diff --git a/po/QML-es.po b/po/QML-es.po
index 6b9fb66d..f9eddd1d 100644
--- a/po/QML-es.po
+++ b/po/QML-es.po
@@ -1,9 +1,15 @@
 msgid ""
 msgstr ""
+"PO-Revision-Date: 2024-01-28 22:01+0000\n"
+"Last-Translator: gallegonovato <fran-carro@hotmail.es>\n"
+"Language-Team: Spanish <https://hosted.weblate.org/projects/jasp/"
+"jaspmachinelearning-qml/es/>\n"
+"Language: es\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=UTF-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+"Plural-Forms: nplurals=2; plural=n != 1;\n"
+"X-Generator: Weblate 5.4-dev\n"
 "X-Language: es\n"
 "X-Source-Language: American English\n"
 "X-Qt-Contexts: true\n"
@@ -3057,9 +3063,11 @@ msgstr ""
 
 msgctxt "FeatureImportance|"
 msgid "Permutations"
-msgstr ""
+msgstr "Permutaciones"
 
 msgctxt "FeatureImportance|"
 msgid ""
 "Sets the number of permutations on which the mean dropout loss is based."
 msgstr ""
+"Establece el número de permutaciones en las que se basa la pérdida media por "
+"abandono."
diff --git a/po/QML-gl.po b/po/QML-gl.po
index 16a9f69a..74db9a7f 100644
--- a/po/QML-gl.po
+++ b/po/QML-gl.po
@@ -1,9 +1,15 @@
 msgid ""
 msgstr ""
+"PO-Revision-Date: 2024-01-28 22:01+0000\n"
+"Last-Translator: ecadrian <ecadrian@hotmail.com>\n"
+"Language-Team: Galician <https://hosted.weblate.org/projects/jasp/"
+"jaspmachinelearning-qml/gl/>\n"
+"Language: gl\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=UTF-8\n"
 "Content-Transfer-Encoding: 8bit\n"
-"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+"Plural-Forms: nplurals=2; plural=n != 1;\n"
+"X-Generator: Weblate 5.4-dev\n"
 "X-Language: gl_ES\n"
 "X-Source-Language: C\n"
 "X-Qt-Contexts: true\n"
@@ -3031,9 +3037,11 @@ msgstr ""
 
 msgctxt "FeatureImportance|"
 msgid "Permutations"
-msgstr ""
+msgstr "Permutacións"
 
 msgctxt "FeatureImportance|"
 msgid ""
 "Sets the number of permutations on which the mean dropout loss is based."
 msgstr ""
+"Establece o número de permutacións nas que se basa a perda media por "
+"abandono."
diff --git a/po/QML-id.po b/po/QML-id.po
index 04c19d77..7e08e9bd 100644
--- a/po/QML-id.po
+++ b/po/QML-id.po
@@ -1,9 +1,15 @@
 msgid ""
 msgstr ""
+"PO-Revision-Date: 2024-01-31 03:54+0000\n"
+"Last-Translator: Rania Rahida <raniarahida@gmail.com>\n"
+"Language-Team: Indonesian <https://hosted.weblate.org/projects/jasp/"
+"jaspmachinelearning-qml/id/>\n"
+"Language: id\n"
 "MIME-Version: 1.0\n"
 "Content-Type: text/plain; charset=UTF-8\n"
 "Content-Transfer-Encoding: 8bit\n"
 "Plural-Forms: nplurals=1; plural=0;\n"
+"X-Generator: Weblate 5.4-dev\n"
 "X-Language: id\n"
 "X-Qt-Contexts: true\n"
 
@@ -65,11 +71,11 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Classification"
-msgstr ""
+msgstr "Klasifikasi"
 
 msgctxt "Description|"
 msgid "Boosting Classification"
-msgstr ""
+msgstr "Meningkatkan Klasifikasi"
 
 msgctxt "Description|"
 msgid "K-Nearest Neighbors Classification"
@@ -77,11 +83,11 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Linear Discriminant"
-msgstr ""
+msgstr "Diskriminan Linier"
 
 msgctxt "Description|"
 msgid "Linear Discriminant Classification"
-msgstr ""
+msgstr "Klasifikasi Diskriminan Linier"
 
 msgctxt "Description|"
 msgid "Neural Network Classification"
@@ -93,11 +99,11 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Clustering"
-msgstr ""
+msgstr "Pengelompokan"
 
 msgctxt "Description|"
 msgid "Density-Based"
-msgstr ""
+msgstr "Berbasis Kepadatan"
 
 msgctxt "Description|"
 msgid "Density-Based Clustering"
@@ -113,11 +119,11 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Hierarchical"
-msgstr ""
+msgstr "Hierarkis"
 
 msgctxt "Description|"
 msgid "Hierarchical Clustering"
-msgstr ""
+msgstr "Pengelompokan Hirarkis"
 
 msgctxt "Description|"
 msgid "Random Forest Clustering"
@@ -125,47 +131,47 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Prediction"
-msgstr ""
+msgstr "Prediksi"
 
 msgctxt "DataSplit|"
 msgid "Data Split Preferences"
-msgstr ""
+msgstr "Preferensi Pemisahan Data"
 
 msgctxt "DataSplit|"
 msgid "Holdout Test Data"
-msgstr ""
+msgstr "Data Uji Daya Tahan"
 
 msgctxt "DataSplit|"
 msgid "Sample"
-msgstr ""
+msgstr "Sampel"
 
 msgctxt "DataSplit|"
 msgid "% of all data"
-msgstr ""
+msgstr "% dari semua data"
 
 msgctxt "DataSplit|"
 msgid "Add generated indicator to data"
-msgstr ""
+msgstr "Menambahkan indikator yang dihasilkan ke data"
 
 msgctxt "DataSplit|"
 msgid "Column name"
-msgstr ""
+msgstr "Nama kolom"
 
 msgctxt "DataSplit|"
 msgid "Test set indicator"
-msgstr ""
+msgstr "Indikator set uji"
 
 msgctxt "DataSplit|"
 msgid "None"
-msgstr ""
+msgstr "Tidak ada"
 
 msgctxt "DataSplit|"
 msgid "Training and Validation Data"
-msgstr ""
+msgstr "Data Pelatihan dan Validasi"
 
 msgctxt "DataSplit|"
 msgid "% for validation data"
-msgstr ""
+msgstr "% untuk data validasi"
 
 msgctxt "DataSplit|"
 msgid "K-fold with"
@@ -173,79 +179,79 @@ msgstr ""
 
 msgctxt "DataSplit|"
 msgid "folds"
-msgstr ""
+msgstr "lipatan"
 
 msgctxt "DataSplit|"
 msgid "Leave-one-out"
-msgstr ""
+msgstr "Tinggalkan-satu-keluar"
 
 msgctxt "ExportResults|"
 msgid "Export Results"
-msgstr ""
+msgstr "Hasil Ekspor"
 
 msgctxt "ExportResults|"
 msgid "Add predictions to data"
-msgstr ""
+msgstr "Menambahkan prediksi ke data"
 
 msgctxt "ExportResults|"
 msgid "Column name"
-msgstr ""
+msgstr "Nama kolom"
 
 msgctxt "ExportResults|"
 msgid "e.g., predicted"
-msgstr ""
+msgstr "misalnya, diprediksi"
 
 msgctxt "ExportResults|"
 msgid "Save as"
-msgstr ""
+msgstr "Simpan sebagai"
 
 msgctxt "ExportResults|"
 msgid "e.g., location/model.jaspML"
-msgstr ""
+msgstr "misalnya, location/model.jaspML"
 
 msgctxt "ExportResults|"
 msgid "Save trained model"
-msgstr ""
+msgstr "Menyimpan model terlatih"
 
 msgctxt "mlClassificationBoosting|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationBoosting|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationBoosting|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationBoosting|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationKnn|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationKnn|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationKnn|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationKnn|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationLda|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationLda|"
 msgid "Coefficients"
-msgstr ""
+msgstr "Koefisien"
 
 msgctxt "mlClassificationLda|"
 msgid "Prior and posterior probabilities"
@@ -257,87 +263,87 @@ msgstr ""
 
 msgctxt "mlClassificationLda|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationLda|"
 msgid "Linear discriminant matrix"
-msgstr ""
+msgstr "Matriks diskriminan linier"
 
 msgctxt "mlClassificationLda|"
 msgid "Densities"
-msgstr ""
+msgstr "Kepadatan"
 
 msgctxt "mlClassificationLda|"
 msgid "Scatter plots"
-msgstr ""
+msgstr "Plot sebar"
 
 msgctxt "mlClassificationLda|"
 msgid "Assumption Checks"
-msgstr ""
+msgstr "Pemeriksaan Asumsi"
 
 msgctxt "mlClassificationLda|"
 msgid "Equality of class means"
-msgstr ""
+msgstr "Kesetaraan kelas berarti"
 
 msgctxt "mlClassificationLda|"
 msgid "Equality of covariance matrices"
-msgstr ""
+msgstr "Kesetaraan matriks kovarians"
 
 msgctxt "mlClassificationLda|"
 msgid "Multicollinearity"
-msgstr ""
+msgstr "Multikolinearitas"
 
 msgctxt "mlClassificationLda|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationLda|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationLda|"
 msgid "Estimation method"
-msgstr ""
+msgstr "Metode estimasi"
 
 msgctxt "mlClassificationNeuralNetwork|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationNeuralNetwork|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationNeuralNetwork|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationNeuralNetwork|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationRandomForest|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationRandomForest|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationRandomForest|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationRandomForest|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "K-distance plot"
@@ -345,91 +351,93 @@ msgstr ""
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Epsilon neighborhood size"
-msgstr ""
+msgstr "Ukuran lingkungan Epsilon"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Min. core points"
-msgstr ""
+msgstr "Min. poin inti"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Distance"
-msgstr ""
+msgstr "Jarak"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Normal"
-msgstr ""
+msgstr "Normal"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Correlated"
-msgstr ""
+msgstr "Berkorelasi"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Model Optimization"
-msgstr ""
+msgstr "Pengoptimalan Model"
 
 msgctxt "mlClusteringDensityBased|"
 msgid "Fixed"
-msgstr ""
+msgstr "Tetap"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Max. iterations"
-msgstr ""
+msgstr "Maks. iterasi"
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid "Fuzziness parameter"
-msgstr ""
+msgstr "Parameter ketidakjelasan"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
+#, fuzzy
 msgctxt "mlClusteringHierarchical|"
 msgid "Dendrogram"
-msgstr ""
+msgstr "Dendrogram"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Distance"
-msgstr ""
+msgstr "Jarak"
 
+#, fuzzy
 msgctxt "mlClusteringHierarchical|"
 msgid "Euclidean"
-msgstr ""
+msgstr "Euclidean"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Pearson"
@@ -437,19 +445,19 @@ msgstr ""
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Linkage"
-msgstr ""
+msgstr "Hubungan"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Average"
-msgstr ""
+msgstr "Rata-rata"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Single"
-msgstr ""
+msgstr "Tunggal"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Complete"
-msgstr ""
+msgstr "Lengkap"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Centroid"
@@ -457,63 +465,65 @@ msgstr ""
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Median"
-msgstr ""
+msgstr "Rata-rata"
 
+#, fuzzy
 msgctxt "mlClusteringHierarchical|"
 msgid "Ward.D"
-msgstr ""
+msgstr "Ward.D"
 
 msgctxt "mlClusteringHierarchical|"
 msgid "Ward.D2"
-msgstr ""
+msgstr "Ward.D2"
 
+#, fuzzy
 msgctxt "mlClusteringHierarchical|"
 msgid "McQuitty"
-msgstr ""
+msgstr "McQuitty"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Max. iterations"
-msgstr ""
+msgstr "Maks. iterasi"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Random sets"
-msgstr ""
+msgstr "Set acak"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Algorithm"
-msgstr ""
+msgstr "Algoritma"
 
 msgctxt "mlClusteringRandomForest|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClusteringRandomForest|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClusteringRandomForest|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClusteringRandomForest|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringRandomForest|"
 msgid "Trees"
@@ -521,139 +531,142 @@ msgstr ""
 
 msgctxt "mlRegressionBoosting|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionBoosting|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionBoosting|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionBoosting|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionBoosting|"
 msgid "Loss function"
-msgstr ""
+msgstr "Fungsi kerugian"
 
 msgctxt "mlRegressionKnn|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionKnn|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionKnn|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionKnn|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionNeuralNetwork|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionNeuralNetwork|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionNeuralNetwork|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionNeuralNetwork|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionRandomForest|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionRandomForest|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionRandomForest|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionRandomForest|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Variable trace"
-msgstr ""
+msgstr "Jejak variabel"
 
+#, fuzzy
 msgctxt "mlRegressionRegularized|"
 msgid "Legend"
-msgstr ""
+msgstr "Legenda"
 
 msgctxt "mlRegressionRegularized|"
 msgid "λ evaluation"
-msgstr ""
+msgstr "Evaluasi λ"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Convergence threshold"
-msgstr ""
+msgstr "Ambang batas konvergensi"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Penalty"
-msgstr ""
+msgstr "Penalti"
 
+#, fuzzy
 msgctxt "mlRegressionRegularized|"
 msgid "Lasso"
-msgstr ""
+msgstr "Lasso"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Ridge"
-msgstr ""
+msgstr "Punggungan"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Elastic net"
-msgstr ""
+msgstr "Bersih elastis"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Elastic net parameter (α)"
-msgstr ""
+msgstr "Parameter bersih elastis (α)"
 
+#, fuzzy
 msgctxt "mlRegressionRegularized|"
 msgid "Lambda (λ)"
-msgstr ""
+msgstr "Lambda (λ)"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Fixed"
-msgstr ""
+msgstr "Tetap"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Optimized"
-msgstr ""
+msgstr "Dioptimalkan"
 
 msgctxt "mlRegressionRegularized|"
 msgid "Largest λ within 1 SE of min"
-msgstr ""
+msgstr "λ terbesar dalam 1 SE dari min"
 
 msgctxt "Description|"
 msgid "Decision Tree"
@@ -665,11 +678,11 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Support Vector Machine"
-msgstr ""
+msgstr "Mesin Vektor Pendukung"
 
 msgctxt "Description|"
 msgid "Support Vector Machine Regression"
-msgstr ""
+msgstr "Regresi Mesin Vektor Pendukung"
 
 msgctxt "Description|"
 msgid "Decision Tree Classification"
@@ -677,59 +690,60 @@ msgstr ""
 
 msgctxt "Description|"
 msgid "Support Vector Machine Classification"
-msgstr ""
+msgstr "Klasifikasi Mesin Vektor Pendukung"
 
 msgctxt "Description|"
 msgid "Neighborhood-Based"
-msgstr ""
+msgstr "Berbasis Lingkungan"
 
 msgctxt "Description|"
 msgid "Neighborhood-Based Clustering"
-msgstr ""
+msgstr "Pengelompokan Berbasis Lingkungan"
 
 msgctxt "mlClassificationDecisionTree|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationDecisionTree|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationDecisionTree|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationDecisionTree|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationSvm|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationSvm|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationSvm|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationSvm|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Center type"
-msgstr ""
+msgstr "Tipe tengah"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Distance"
-msgstr ""
+msgstr "Jarak"
 
+#, fuzzy
 msgctxt "mlClusteringKMeans|"
 msgid "Euclidean"
-msgstr ""
+msgstr "Euclidean"
 
 msgctxt "mlClusteringKMeans|"
 msgid "Manhattan"
@@ -737,71 +751,71 @@ msgstr ""
 
 msgctxt "mlRegressionDecisionTree|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionDecisionTree|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionDecisionTree|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionDecisionTree|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionSvm|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionSvm|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionSvm|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionSvm|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlPrediction|"
 msgid "Trained model"
-msgstr ""
+msgstr "Model terlatih"
 
 msgctxt "mlPrediction|"
 msgid "e.g., location/model.jaspML"
-msgstr ""
+msgstr "misalnya, location/model.jaspML"
 
 msgctxt "mlPrediction|"
 msgid "Features"
-msgstr ""
+msgstr "Fitur"
 
 msgctxt "mlPrediction|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlPrediction|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlPrediction|"
 msgid "to"
-msgstr ""
+msgstr "untuk"
 
 msgctxt "Description|"
 msgid "Linear"
-msgstr ""
+msgstr "Linier"
 
 msgctxt "Description|"
 msgid "Linear Regression"
-msgstr ""
+msgstr "Regresi Linier"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Shrinkage"
-msgstr ""
+msgstr "Penyusutan"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
@@ -809,10 +823,14 @@ msgid ""
 "the learning rate or step-size reduction 0.001 to 0.1 usually work, but a "
 "smaller learning rate typically requires more trees."
 msgstr ""
+"Parameter penyusutan yang diterapkan pada setiap pohon dalam ekspansi. Juga "
+"dikenal sebagai laju pembelajaran atau pengurangan ukuran langkah 0,001 "
+"hingga 0,1 biasanya berfungsi, tetapi laju pembelajaran yang lebih kecil "
+"biasanya membutuhkan lebih banyak pohon."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Interaction depth"
-msgstr ""
+msgstr "Kedalaman interaksi"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
@@ -820,10 +838,14 @@ msgid ""
 "of variable interactions allowed. A value of 1 implies an additive model, a "
 "value of 2 implies a model with up to 2-way interactions, etc. Default is 1."
 msgstr ""
+"Bilangan bulat yang menentukan kedalaman maksimum setiap pohon (yaitu, "
+"tingkat interaksi variabel tertinggi yang diperbolehkan. Nilai 1 "
+"mengimplikasikan model aditif, nilai 2 mengimplikasikan model dengan "
+"interaksi hingga 2 arah, dst. Nilai default adalah 1."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Min. observations in node"
-msgstr ""
+msgstr "Min. pengamatan dalam simpul"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
@@ -831,116 +853,130 @@ msgid ""
 "of the trees. Note that this is the actual number of observations, not the "
 "total weight."
 msgstr ""
+"Bilangan bulat yang menentukan jumlah minimum pengamatan pada simpul "
+"terminal pohon. Perhatikan bahwa ini adalah jumlah observasi yang "
+"sebenarnya, bukan total bobot."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Training data used per tree"
-msgstr ""
+msgstr "Data pelatihan yang digunakan per pohon"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
 "Select the percentage of training data that is used to train each individual "
 "tree."
 msgstr ""
+"Pilih persentase data pelatihan yang digunakan untuk melatih setiap pohon."
 
 msgctxt "Deviance|"
 msgid "Deviance"
-msgstr ""
+msgstr "Penyimpangan"
 
 msgctxt "Deviance|"
 msgid "Shows the prediction error plotted against the number of trees."
-msgstr ""
+msgstr "Menunjukkan kesalahan prediksi yang diplot terhadap jumlah pohon."
 
 msgctxt "ModelOptimization|"
 msgid "Number of Trees"
-msgstr ""
+msgstr "Jumlah Pohon"
 
 msgctxt "ModelOptimization|"
 msgid "Choose how to optimize the model."
-msgstr ""
+msgstr "Pilih cara mengoptimalkan model."
 
 msgctxt "ModelOptimization|"
 msgid "Fixed"
-msgstr ""
+msgstr "Tetap"
 
 msgctxt "ModelOptimization|"
 msgid "Enables you to use a user-specified number of decision trees."
 msgstr ""
+"Memungkinkan Anda menggunakan jumlah pohon keputusan yang ditentukan "
+"pengguna."
 
 msgctxt "ModelOptimization|"
 msgid "Trees"
-msgstr ""
+msgstr "Pohon"
 
 msgctxt "ModelOptimization|"
 msgid "The number of trees."
-msgstr ""
+msgstr "Jumlah pohon."
 
 msgctxt "ModelOptimization|"
 msgid "Optimized"
-msgstr ""
+msgstr "Dioptimalkan"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Enables you to optimize the prediction error on a validation data set with "
 "respect to the number of trees."
 msgstr ""
+"Memungkinkan Anda untuk mengoptimalkan kesalahan prediksi pada kumpulan data "
+"validasi sehubungan dengan jumlah pohon."
 
 msgctxt "ModelOptimization|"
 msgid "Max. trees"
-msgstr ""
+msgstr "Maks. pohon"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Sets the maximum number of possible decision trees to be considered. At "
 "default, this is set to 100."
 msgstr ""
+"Mengatur jumlah maksimum pohon keputusan yang mungkin dipertimbangkan. "
+"Secara default, ini diatur ke 100."
 
 msgctxt "Oob|"
 msgid "Out-of-bag improvement"
-msgstr ""
+msgstr "Peningkatan di luar kantong"
 
 msgctxt "Oob|"
 msgid ""
 "Plots the number of trees against the out-of-bag classification accuracy "
 "improvement of the model. Accuracy is assessed for the training set."
 msgstr ""
+"Memplot jumlah pohon terhadap peningkatan akurasi klasifikasi di luar "
+"kantong dari model. Akurasi dinilai untuk set pelatihan."
 
 msgctxt "RelativeInfluence|"
 msgid "Relative influence"
-msgstr ""
+msgstr "Pengaruh relatif"
 
 msgctxt "RelativeInfluence|"
 msgid "Shows the relative influence of the features."
-msgstr ""
+msgstr "Menunjukkan pengaruh relatif dari fitur."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Min. observations for split"
-msgstr ""
+msgstr "Min. pengamatan untuk pemisahan"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
 "The minimum number of observations that must exist in a node in order for a "
 "split to be attempted."
 msgstr ""
+"Jumlah minimum observasi yang harus ada dalam sebuah node agar pemisahan "
+"dapat dilakukan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Min. observations in terminal"
-msgstr ""
+msgstr "Min. pengamatan di terminal"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The minimum number of observations in any terminal node."
-msgstr ""
+msgstr "Jumlah minimum pengamatan di simpul terminal mana pun."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Max. interaction depth"
-msgstr ""
+msgstr "Maks. kedalaman interaksi"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Set the maximum depth of any node of the final tree."
-msgstr ""
+msgstr "Mengatur kedalaman maksimum dari setiap simpul pada pohon akhir."
 
 msgctxt "AttemptedSplits|"
 msgid "Attempted splits"
-msgstr ""
+msgstr "Percobaan pemisahan"
 
 msgctxt "AttemptedSplits|"
 msgid ""
@@ -949,14 +985,18 @@ msgid ""
 "positive weight) sent left or right by the split. It also shows the "
 "improvement in deviance given by the splits."
 msgstr ""
+"Menunjukkan pemisahan yang dilakukan oleh algoritma, fitur dan titik "
+"pemisahan yang sesuai, dan jumlah pengamatan (yang tidak hilang dan memiliki "
+"bobot positif) yang dikirim ke kiri atau ke kanan oleh pemisahan. Ini juga "
+"menunjukkan peningkatan penyimpangan yang diberikan oleh pemisahan."
 
 msgctxt "AttemptedSplits|"
 msgid "Only show splits in tree"
-msgstr ""
+msgstr "Hanya menampilkan pemisahan di pohon"
 
 msgctxt "AttemptedSplits|"
 msgid "Remove splits that do not occur in the final tree from the table."
-msgstr ""
+msgstr "Hapus pemisahan yang tidak terjadi di pohon akhir dari tabel."
 
 msgctxt "TreePlot|"
 msgid "Decision tree"
@@ -968,23 +1008,25 @@ msgstr ""
 
 msgctxt "AlgorithmicSettings|"
 msgid "Weights"
-msgstr ""
+msgstr "Bobot"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Rectangular"
-msgstr ""
+msgstr "Persegi panjang"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Triangular"
-msgstr ""
+msgstr "Segitiga"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Epanechnikov"
-msgstr ""
+msgstr "Epanechnikov"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Biweight"
-msgstr ""
+msgstr "Biweight"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Triweight"
@@ -992,11 +1034,11 @@ msgstr ""
 
 msgctxt "AlgorithmicSettings|"
 msgid "Cosine"
-msgstr ""
+msgstr "Cosinus"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Inverse"
-msgstr ""
+msgstr "Kebalikannya"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Gaussian"
@@ -1004,11 +1046,12 @@ msgstr ""
 
 msgctxt "AlgorithmicSettings|"
 msgid "Rank"
-msgstr ""
+msgstr "Peringkat"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Optimal"
-msgstr ""
+msgstr "Optimal"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
@@ -1016,10 +1059,13 @@ msgid ""
 "option results in standard knn, while the other options expand the algorithm "
 "by weighing the nearest neighbors. See also the kknn package."
 msgstr ""
+"Mengatur skema pembobotan untuk tetangga terdekat. Opsi persegi panjang "
+"default menghasilkan knn standar, sementara opsi lainnya memperluas "
+"algoritme dengan menimbang tetangga terdekat. Lihat juga paket kknn."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Distance"
-msgstr ""
+msgstr "Jarak"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Euclidian"
@@ -1034,6 +1080,8 @@ msgid ""
 "The distance metric to be used when determining the similarity between "
 "nearest neighbors. Can be either Euclidean or Manhattan distance."
 msgstr ""
+"Metrik jarak yang akan digunakan saat menentukan kemiripan antara tetangga "
+"terdekat. Dapat berupa jarak Euclidean atau Manhattan."
 
 #, fuzzy
 msgctxt "ModelOptimization|"
@@ -1070,11 +1118,11 @@ msgstr ""
 
 msgctxt "OptimPlot|"
 msgid "Mean squared error"
-msgstr ""
+msgstr "Rata-rata kesalahan kuadrat"
 
 msgctxt "OptimPlot|"
 msgid "Classification accuracy"
-msgstr ""
+msgstr "Akurasi klasifikasi"
 
 msgctxt "OptimPlot|"
 msgid ""
@@ -1084,62 +1132,69 @@ msgid ""
 "classification accuracy of the model. Accuracy is assessed for the training "
 "(and validation) set."
 msgstr ""
+"Untuk regresi, memplot jumlah tetangga terdekat terhadap MSE model. Akurasi "
+"dinilai untuk set pelatihan (dan validasi). Untuk klasifikasi, memplot "
+"jumlah tetangga terdekat terhadap akurasi klasifikasi model. Akurasi dinilai "
+"untuk set pelatihan (dan validasi)."
 
 msgctxt "WeightFunction|"
 msgid "Weight function"
-msgstr ""
+msgstr "Fungsi berat badan"
 
 msgctxt "WeightFunction|"
 msgid "Shows how the weights are assigned as a function of the distance."
-msgstr ""
+msgstr "Menunjukkan bagaimana bobot ditetapkan sebagai fungsi jarak."
 
 msgctxt "ActivationFunctionPlot|"
 msgid "Activation function"
-msgstr ""
+msgstr "Fungsi aktivasi"
 
 msgctxt "ActivationFunctionPlot|"
 msgid "Creates a plot of the activation function."
-msgstr ""
+msgstr "Membuat plot fungsi aktivasi."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Activation function"
-msgstr ""
+msgstr "Fungsi aktivasi"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Linear"
-msgstr ""
+msgstr "Linier"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Binary"
-msgstr ""
+msgstr "Biner"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Logistic sigmoid"
-msgstr ""
+msgstr "Sigmoid logistik"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Sine"
-msgstr ""
+msgstr "Sinus"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Inverse tangent"
-msgstr ""
+msgstr "Garis singgung terbalik"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Hyperbolic tangent"
-msgstr ""
+msgstr "Garis singgung hiperbolik"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "ReLU"
-msgstr ""
+msgstr "ReLU"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Softplus"
-msgstr ""
+msgstr "Softplus"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Softsign"
-msgstr ""
+msgstr "Softsign"
 
 msgctxt "AlgorithmicSettings|"
 msgid "ELU"
@@ -1182,10 +1237,28 @@ msgid ""
 "- Gaussian: *f(x) = e * (-x^2)*\n"
 "- GeLU: *f(x) = 0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))*"
 msgstr ""
+"Mengatur fungsi aktivasi untuk sinyal di setiap lapisan tersembunyi. Opsi "
+"yang tersedia adalah:\n"
+"- linier: *f(x) = x*\n"
+"- Biner: *f(x) = 0 jika x < 0, 1 jika x > 0\n"
+"- Sigmoid logistik: *f(x) = 1 / (1 + e^(-x))*\n"
+"- Sinus *f(x) = sin(x)*\n"
+"- Cosinus: *f(x) = cos(x)*\n"
+"- Garis singgung terbalik: *f(x) = arctan(x)*\n"
+"- Garis singgung hiperbolik: *f(x) = tanh(x)*\n"
+"- ReLU: *f(x) = 0 jika x < 0, x jika x > 0*\n"
+"- Softplus: *f(x) = log(1 + e^x)*\n"
+"- Softsign: *f(x) = x / (abs(x) + 1)*\n"
+"- ELU: *f(x) = e^x - 1 jika x <= 0, x jika x > 0*\n"
+"- LReLU: *f(x) = 0.01 * x jika x < 0, x jika x > 0*\n"
+"- SiLU: *f(x) = x / (1 + e^(-x))*\n"
+"- Mish: *f(x) = x * tanh(log(1 + e^x))*\n"
+"- Gaussian: *f(x) = e * (-x^2)*\n"
+"- GeLU: *f(x) = 0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))))"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Algorithm"
-msgstr ""
+msgstr "Algoritma"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Backpropagation"
@@ -1221,170 +1294,172 @@ msgstr ""
 
 msgctxt "AlgorithmicSettings|"
 msgid "Learning rate"
-msgstr ""
+msgstr "Tingkat pembelajaran"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The learning rate used by the backpropagation algorithm."
-msgstr ""
+msgstr "Laju pembelajaran yang digunakan oleh algoritma backpropagation."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Loss function"
-msgstr ""
+msgstr "Fungsi kerugian"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Sum of squares"
-msgstr ""
+msgstr "Jumlah kuadrat"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Cross-entropy"
-msgstr ""
+msgstr "Entropi silang"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The loss function used."
-msgstr ""
+msgstr "Fungsi kehilangan yang digunakan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Stopping criteria loss function"
-msgstr ""
+msgstr "Menghentikan fungsi kehilangan kriteria"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
 "The threshold for the partial derivatives of the error function as stopping "
 "criteria."
 msgstr ""
+"Ambang batas untuk turunan parsial dari fungsi kesalahan sebagai kriteria "
+"penghentian."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Max. training repetitions"
-msgstr ""
+msgstr "Maks. pengulangan pelatihan"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The maximum number of repetitions used in training the network."
-msgstr ""
+msgstr "Jumlah pengulangan maksimum yang digunakan dalam melatih jaringan."
 
 msgctxt "Coefficients|"
 msgid "Network weights"
-msgstr ""
+msgstr "Bobot jaringan"
 
 msgctxt "Coefficients|"
 msgid ""
 "Shows the connections in the neural network together with their weights."
-msgstr ""
+msgstr "Menunjukkan koneksi dalam jaringan saraf bersama dengan bobotnya."
 
 msgctxt "ModelOptimization|"
 msgid "Network Topology"
-msgstr ""
+msgstr "Topologi Jaringan"
 
 msgctxt "ModelOptimization|"
 msgid "Manual"
-msgstr ""
+msgstr "Manual"
 
 msgctxt "ModelOptimization|"
 msgid "Specify the nodes in each hidden layer of the neural network."
-msgstr ""
+msgstr "Tentukan node di setiap lapisan tersembunyi jaringan saraf."
 
 msgctxt "ModelOptimization|"
 msgid "Nodes"
-msgstr ""
+msgstr "Simpul"
 
 msgctxt "ModelOptimization|"
 msgid "Hidden layer "
-msgstr ""
+msgstr "Lapisan tersembunyi "
 
 msgctxt "ModelOptimization|"
 msgid "Optimize the topology of the network using a genetic algorithm."
-msgstr ""
+msgstr "Mengoptimalkan topologi jaringan menggunakan algoritma genetika."
 
 msgctxt "ModelOptimization|"
 msgid "Population size"
-msgstr ""
+msgstr "Ukuran populasi"
 
 msgctxt "ModelOptimization|"
 msgid "Size of population used in genetic optimization."
-msgstr ""
+msgstr "Ukuran populasi yang digunakan dalam optimasi genetik."
 
 msgctxt "ModelOptimization|"
 msgid "Generations"
-msgstr ""
+msgstr "Generasi"
 
 msgctxt "ModelOptimization|"
 msgid "Number of generations used in genetic optimization."
-msgstr ""
+msgstr "Jumlah generasi yang digunakan dalam optimasi genetik."
 
 msgctxt "ModelOptimization|"
 msgid "Max. number of layers"
-msgstr ""
+msgstr "Maks. jumlah lapisan"
 
 msgctxt "ModelOptimization|"
 msgid "Max. nodes in each layer"
-msgstr ""
+msgstr "Maks. node di setiap lapisan"
 
 msgctxt "ModelOptimization|"
 msgid "Parent selection"
-msgstr ""
+msgstr "Pemilihan induk"
 
 msgctxt "ModelOptimization|"
 msgid "Roulette wheel"
-msgstr ""
+msgstr "Roda roulette"
 
 msgctxt "ModelOptimization|"
 msgid "Universal"
-msgstr ""
+msgstr "Universal"
 
 msgctxt "ModelOptimization|"
 msgid "Rank"
-msgstr ""
+msgstr "Peringkat"
 
 msgctxt "ModelOptimization|"
 msgid "Tournament"
-msgstr ""
+msgstr "Turnamen"
 
 msgctxt "ModelOptimization|"
 msgid "Random"
-msgstr ""
+msgstr "Acak"
 
 msgctxt "ModelOptimization|"
 msgid "How to select suviving networks."
-msgstr ""
+msgstr "Cara memilih jaringan yang selamat."
 
 msgctxt "ModelOptimization|"
 msgid "Candidates"
-msgstr ""
+msgstr "Kandidat"
 
 msgctxt "ModelOptimization|"
 msgid "Number of candidates for tournament selection"
-msgstr ""
+msgstr "Jumlah kandidat untuk pemilihan turnamen"
 
 msgctxt "ModelOptimization|"
 msgid "Crossover method"
-msgstr ""
+msgstr "Metode persilangan"
 
 msgctxt "ModelOptimization|"
 msgid "Uniform"
-msgstr ""
+msgstr "Seragam"
 
 msgctxt "ModelOptimization|"
 msgid "One-point"
-msgstr ""
+msgstr "Satu poin"
 
 msgctxt "ModelOptimization|"
 msgid "Multi-point"
-msgstr ""
+msgstr "Multi-poin"
 
 msgctxt "ModelOptimization|"
 msgid "How to crossover two candidate networks."
-msgstr ""
+msgstr "Cara menyilangkan dua jaringan kandidat."
 
 msgctxt "ModelOptimization|"
 msgid "Mutations"
-msgstr ""
+msgstr "Mutasi"
 
 msgctxt "ModelOptimization|"
 msgid "Reset"
-msgstr ""
+msgstr "Atur ulang"
 
 msgctxt "ModelOptimization|"
 msgid "Swap"
-msgstr ""
+msgstr "Tukar"
 
 msgctxt "ModelOptimization|"
 msgid "Scramble"
@@ -1392,57 +1467,59 @@ msgstr ""
 
 msgctxt "ModelOptimization|"
 msgid "Inversion"
-msgstr ""
+msgstr "Pembalikan"
 
 msgctxt "ModelOptimization|"
 msgid "How to mutate a network."
-msgstr ""
+msgstr "Cara melakukan mutasi jaringan."
 
 msgctxt "ModelOptimization|"
 msgid "Probability"
-msgstr ""
+msgstr "Probabilitas"
 
 msgctxt "ModelOptimization|"
 msgid "The mutation probability of a random network in each generation."
-msgstr ""
+msgstr "Probabilitas mutasi dari jaringan acak di setiap generasi."
 
 msgctxt "ModelOptimization|"
 msgid "Survival method"
-msgstr ""
+msgstr "Metode bertahan hidup"
 
 msgctxt "ModelOptimization|"
 msgid "Fitness-based"
-msgstr ""
+msgstr "Berbasis kebugaran"
 
 msgctxt "ModelOptimization|"
 msgid "Age-based"
-msgstr ""
+msgstr "Berdasarkan usia"
 
 msgctxt "ModelOptimization|"
 msgid "How to choose which networks survive and die in a generation."
 msgstr ""
+"Bagaimana memilih jaringan mana yang bertahan dan mati dalam satu generasi."
 
 msgctxt "ModelOptimization|"
 msgid "Elitism"
-msgstr ""
+msgstr "Elitisme"
 
 msgctxt "ModelOptimization|"
 msgid "Keep top networks from dying out."
-msgstr ""
+msgstr "Jaga agar jaringan teratas tidak mati."
 
 msgctxt "ModelOptimization|"
 msgid "Percentage of top networks to keep."
-msgstr ""
+msgstr "Persentase jaringan teratas yang harus dipertahankan."
 
 msgctxt "NetworkPlot|"
 msgid "Network structure"
-msgstr ""
+msgstr "Struktur jaringan"
 
 msgctxt "NetworkPlot|"
 msgid ""
 "Creates a plot that visualizes the structure (nodes and edges) of the "
 "network."
 msgstr ""
+"Membuat plot yang memvisualisasikan struktur (simpul dan tepi) jaringan."
 
 msgctxt "OptimPlot|"
 msgid ""
@@ -1453,131 +1530,146 @@ msgid ""
 "generations in the evoluationary optimization algorithm. Accuracy is "
 "assessed for the training (and validation) set."
 msgstr ""
+"Untuk regresi, memplot rata-rata kesalahan kuadrat rata-rata dari populasi "
+"jaringan saraf terhadap jumlah generasi dalam algoritma optimasi "
+"evolusioner. Untuk klasifikasi, memplot akurasi klasifikasi rata-rata dari "
+"populasi jaringan saraf terhadap jumlah generasi dalam algoritma optimasi "
+"evolusioner. Akurasi dinilai untuk set pelatihan (dan validasi)."
 
 msgctxt "AccuracyDecrease|"
 msgid "Mean decrease in accuracy"
-msgstr ""
+msgstr "Penurunan rata-rata dalam akurasi"
 
 msgctxt "AccuracyDecrease|"
 msgid ""
 "Displays a figure with the mean decrease in accuracy per feature in the "
 "model."
 msgstr ""
+"Menampilkan angka dengan rata-rata penurunan akurasi per fitur dalam model."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Features per split"
-msgstr ""
+msgstr "Fitur per pemisahan"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Auto"
-msgstr ""
+msgstr "Otomatis"
 
 msgctxt "AlgorithmicSettings|"
 msgid "Manual"
-msgstr ""
+msgstr "Manual"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
 "Set the number of feature variables that is used within each split in the "
 "decision trees. Defaults to auto."
 msgstr ""
+"Mengatur jumlah variabel fitur yang digunakan dalam setiap pembagian dalam "
+"pohon keputusan. Nilai defaultnya adalah otomatis."
 
 msgctxt "AlgorithmicSettings|"
 msgid "The number of feature variables in each split."
-msgstr ""
+msgstr "Jumlah variabel fitur dalam setiap pemisahan."
 
 msgctxt "ModelOptimization|"
 msgid "The number of trees to be used."
-msgstr ""
+msgstr "Jumlah pohon yang akan digunakan."
 
 msgctxt "NodePurity|"
 msgid "Total increase in node purity"
-msgstr ""
+msgstr "Peningkatan total dalam kemurnian simpul"
 
 msgctxt "NodePurity|"
 msgid ""
 "Displays a figure with total increase in node purity per feature in the "
 "model."
 msgstr ""
+"Menampilkan angka dengan total peningkatan kemurnian simpul per fitur dalam "
+"model."
 
 msgctxt "Oob|"
 msgid "Out-of-bag error"
-msgstr ""
+msgstr "Kesalahan di luar kantong"
 
 msgctxt "Oob|"
 msgid "Out-of-bag accuracy"
-msgstr ""
+msgstr "Akurasi di luar kantong"
 
 msgctxt "Oob|"
 msgid ""
 "Plots the number of trees against the out-of-bag mean squared error "
 "(regression) or accuracy (classification) of the model."
 msgstr ""
+"Memplot jumlah pohon terhadap kesalahan kuadrat rata-rata di luar kantong "
+"(regresi) atau akurasi (klasifikasi) model."
 
 msgctxt "CoefficientTable|"
 msgid "Coefficients"
-msgstr ""
+msgstr "Koefisien"
 
 msgctxt "CoefficientTable|"
 msgid "Shows a table containing the regression coefficients."
-msgstr ""
+msgstr "Menampilkan tabel yang berisi koefisien regresi."
 
 msgctxt "CoefficientTable|"
 msgid "Confidence interval"
-msgstr ""
+msgstr "Interval kepercayaan"
 
 msgctxt "CoefficientTable|"
 msgid "Display confidence intervals around estimated regression coefficients."
-msgstr ""
+msgstr "Menampilkan interval kepercayaan di sekitar estimasi koefisien regresi."
 
 msgctxt "CoefficientTable|"
 msgid "The confidence level for the interval."
-msgstr ""
+msgstr "Tingkat kepercayaan untuk interval."
 
 msgctxt "CoefficientTable|"
 msgid "Display equation"
-msgstr ""
+msgstr "Persamaan tampilan"
 
 msgctxt "CoefficientTable|"
 msgid ""
 "Display the regression equation with the estimated values of the "
 "coefficients."
-msgstr ""
+msgstr "Menampilkan persamaan regresi dengan nilai estimasi koefisien."
 
 msgctxt "Intercept|"
 msgid "Include intercept"
-msgstr ""
+msgstr "Termasuk mencegat"
 
 msgctxt "Intercept|"
 msgid "Whether to include an intercept in the regression formula."
-msgstr ""
+msgstr "Apakah akan menyertakan intersep dalam rumus regresi."
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid "Target"
-msgstr ""
+msgstr "Sasaran"
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid "In this box, the variable that needs to be predicted should be entered."
-msgstr ""
+msgstr "Di dalam kotak ini, variabel yang perlu diprediksi harus dimasukkan."
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid "Features"
-msgstr ""
+msgstr "Fitur"
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid ""
 "In this box, the variables that provide information about the target "
 "variable should be entered."
 msgstr ""
+"Pada kotak ini, variabel-variabel yang memberikan informasi mengenai "
+"variabel sasaran harus dimasukkan."
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid "Weights"
-msgstr ""
+msgstr "Bobot"
 
 msgctxt "VariablesFormRegularizedRegression|"
 msgid ""
 "In this box, an optional variable containing case weights can be entered."
 msgstr ""
+"Dalam kotak ini, variabel opsional yang berisi bobot huruf dapat dimasukkan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Radial"
@@ -1585,49 +1677,52 @@ msgstr ""
 
 msgctxt "AlgorithmicSettings|"
 msgid "Polynomial"
-msgstr ""
+msgstr "Polinomial"
 
+#, fuzzy
 msgctxt "AlgorithmicSettings|"
 msgid "Sigmoid"
-msgstr ""
+msgstr "Sigmoid"
 
 msgctxt "AlgorithmicSettings|"
 msgid ""
 "The kernel used in training and predicting. Possible kernels are 'linear', "
 "'radial', 'polynomial', and 'sigmoid'."
 msgstr ""
+"Kernel yang digunakan dalam pelatihan dan prediksi. Kernel yang memungkinkan "
+"adalah 'linear', 'radial', 'polinomial', dan 'sigmoid'."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Degree"
-msgstr ""
+msgstr "Derajat"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The degree of polynomial used."
-msgstr ""
+msgstr "Derajat polinomial yang digunakan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Gamma parameter"
-msgstr ""
+msgstr "Parameter gamma"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The gamma parameter used."
-msgstr ""
+msgstr "Parameter gamma yang digunakan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "r parameter"
-msgstr ""
+msgstr "parameter r"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The complexity parameter used."
-msgstr ""
+msgstr "Parameter kompleksitas yang digunakan."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Tolerance of termination criterion"
-msgstr ""
+msgstr "Toleransi terhadap kriteria penghentian"
 
 msgctxt "AlgorithmicSettings|"
 msgid "The tolerance of termination criterion."
-msgstr ""
+msgstr "Toleransi kriteria penghentian."
 
 msgctxt "AlgorithmicSettings|"
 msgid "Epsilon"
@@ -1639,90 +1734,102 @@ msgstr ""
 
 msgctxt "SupportVectors|"
 msgid "Support vectors"
-msgstr ""
+msgstr "Vektor pendukung"
 
 msgctxt "SupportVectors|"
 msgid ""
 "Shows a table containing the data (points) indicated as support vectors by "
 "the algorithm."
 msgstr ""
+"Menampilkan tabel yang berisi data (titik) yang diindikasikan sebagai vektor "
+"dukungan oleh algoritme."
 
 msgctxt "AndrewsCurve|"
 msgid "Andrews curves"
-msgstr ""
+msgstr "Kurva Andrews"
 
 msgctxt "AndrewsCurve|"
 msgid ""
 "Is a way to visualize structure in high-dimensional data. Lines that cluster "
 "are observations that are more alike."
 msgstr ""
+"Merupakan cara untuk memvisualisasikan struktur dalam data berdimensi "
+"tinggi. Garis-garis yang mengelompok adalah pengamatan yang lebih mirip."
 
 msgctxt "ClusterDensity|"
 msgid "Cluster densities"
-msgstr ""
+msgstr "Kepadatan klaster"
 
 msgctxt "ClusterDensity|"
 msgid ""
 "For each feature variable, generates a plot showing the overlapping "
 "densities for the clusters."
 msgstr ""
+"Untuk setiap variabel fitur, buatlah plot yang menunjukkan kepadatan yang "
+"tumpang tindih untuk klaster."
 
 msgctxt "ClusterDensity|"
 msgid "Group into one figure"
-msgstr ""
+msgstr "Kelompokkan menjadi satu gambar"
 
 msgctxt "ClusterDensity|"
 msgid "Group the density plots per feature into a single figure."
-msgstr ""
+msgstr "Kelompokkan plot densitas per fitur ke dalam satu gambar."
 
 msgctxt "ClusterMatrix|"
 msgid "Cluster matrix plot"
-msgstr ""
+msgstr "Plot matriks cluster"
 
 msgctxt "ClusterMatrix|"
 msgid ""
 "Creates a *n* x *n* plot that visualizes to which cluster every observation "
 "belongs according to the current model."
 msgstr ""
+"Membuat plot *n* x *n* yang memvisualisasikan ke klaster mana setiap "
+"pengamatan berada menurut model saat ini."
 
 msgctxt "ClusterMeans|"
 msgid "Cluster means"
-msgstr ""
+msgstr "Klaster berarti"
 
 msgctxt "ClusterMeans|"
 msgid ""
 "Creates a plot that visualizes and compares the mean of the feature "
 "variables in each cluster."
 msgstr ""
+"Membuat plot yang memvisualisasikan dan membandingkan rata-rata variabel "
+"fitur di setiap klaster."
 
 msgctxt "ClusterMeans|"
 msgid "Display barplot"
-msgstr ""
+msgstr "Menampilkan diagram batang"
 
 msgctxt "ClusterMeans|"
 msgid "Transform the cluster mean figure into a barplot."
-msgstr ""
+msgstr "Ubah angka rata-rata klaster menjadi diagram batang."
 
 msgctxt "ClusterMeans|"
 msgid "Group into one figure"
-msgstr ""
+msgstr "Kelompokkan menjadi satu gambar"
 
 msgctxt "ClusterMeans|"
 msgid "Group the plots per feature into a single figure."
-msgstr ""
+msgstr "Kelompokkan plot per fitur ke dalam satu gambar."
 
 msgctxt "DataSplit|"
 msgid "Data split"
-msgstr ""
+msgstr "Pemisahan data"
 
 msgctxt "DataSplit|"
 msgid ""
 "Shows how the data is split into training (and validation), and test set."
 msgstr ""
+"Menunjukkan bagaimana data dibagi menjadi pelatihan (dan validasi), dan set "
+"pengujian."
 
 msgctxt "DecisionBoundary|"
 msgid "Decision boundary matrix"
-msgstr ""
+msgstr "Matriks batas keputusan"
 
 msgctxt "DecisionBoundary|"
 msgid ""
@@ -1730,26 +1837,30 @@ msgid ""
 "classified if predicted through the current model. Boundaries between "
 "classes are visualized. Can only be made for numeric features."
 msgstr ""
+"Membuat plot *n* x *n* yang memvisualisasikan bagaimana setiap pengamatan "
+"akan diklasifikasikan jika diprediksi melalui model saat ini. Batas-batas "
+"antar kelas divisualisasikan. Hanya dapat dibuat untuk fitur numerik."
 
 msgctxt "DecisionBoundary|"
 msgid "Legend"
-msgstr ""
+msgstr "Legenda"
 
 msgctxt "DecisionBoundary|"
 msgid "Show a legend next to the figure."
-msgstr ""
+msgstr "Menampilkan legenda di samping gambar."
 
 msgctxt "DecisionBoundary|"
 msgid "Add data points"
-msgstr ""
+msgstr "Menambahkan poin data"
 
 msgctxt "DecisionBoundary|"
 msgid "Show the observations in the data set as points in the plot."
 msgstr ""
+"Tampilkan pengamatan dalam kumpulan data sebagai titik-titik dalam plot."
 
 msgctxt "ElbowMethod|"
 msgid "Elbow method"
-msgstr ""
+msgstr "Metode siku"
 
 msgctxt "ElbowMethod|"
 msgid ""
@@ -1758,24 +1869,32 @@ msgid ""
 "optimal number of clusters. The plot shows three curves using AIC, BIC, and "
 "'elbow method' optimization."
 msgstr ""
+"Menghasilkan plot dengan jumlah total dalam jumlah kuadrat pada sumbu y dan "
+"jumlah cluster pada sumbu x. Plot ini dapat digunakan untuk menentukan "
+"jumlah cluster yang optimal. Plot ini menunjukkan tiga kurva dengan "
+"menggunakan optimasi AIC, BIC, dan 'metode siku'."
 
 msgctxt "PredictivePerformance|"
 msgid "Predictive performance"
-msgstr ""
+msgstr "Kinerja prediktif"
 
 msgctxt "PredictivePerformance|"
 msgid ""
 "Plots the true values of the observations in the test set against their "
 "predicted values."
 msgstr ""
+"Memplot nilai sebenarnya dari pengamatan dalam set pengujian terhadap nilai "
+"prediksinya."
 
 msgctxt "RocCurve|"
 msgid "ROC curves"
-msgstr ""
+msgstr "Kurva ROC"
 
 msgctxt "RocCurve|"
 msgid "Displays ROC curves for each class predicted against all other classes."
 msgstr ""
+"Menampilkan kurva ROC untuk setiap kelas yang diprediksi terhadap semua "
+"kelas lainnya."
 
 msgctxt "Tsne|"
 msgid "t-SNE cluster plot"
@@ -1795,35 +1914,38 @@ msgstr ""
 
 msgctxt "Tsne|"
 msgid "Legend"
-msgstr ""
+msgstr "Legenda"
 
 msgctxt "Tsne|"
 msgid "Show a legend next to the figure."
-msgstr ""
+msgstr "Menampilkan legenda di samping gambar."
 
 msgctxt "Tsne|"
 msgid "Add data labels"
-msgstr ""
+msgstr "Menambahkan label data"
 
 msgctxt "Tsne|"
 msgid ""
 "Add the row numbers of the observations in the data set as labels to the "
 "plot."
 msgstr ""
+"Tambahkan nomor baris pengamatan dalam kumpulan data sebagai label pada plot."
 
 msgctxt "ClassProportions|"
 msgid "Class proportions"
-msgstr ""
+msgstr "Proporsi kelas"
 
 msgctxt "ClassProportions|"
 msgid ""
 "Displays a table that shows the proportions of each class in the data set, "
 "training (and validaton), and test set."
 msgstr ""
+"Menampilkan tabel yang menunjukkan proporsi setiap kelas dalam kumpulan "
+"data, pelatihan (dan validasi), dan kumpulan tes."
 
 msgctxt "ClusterInfo|"
 msgid "Cluster information"
-msgstr ""
+msgstr "Informasi klaster"
 
 msgctxt "ClusterInfo|"
 msgid ""
@@ -1832,113 +1954,132 @@ msgid ""
 "divided by its total over the various clusters. These outputs are shown by "
 "default."
 msgstr ""
+"Menampilkan ukuran setiap klaster dan proporsi yang dijelaskan dari "
+"heterogenitas dalam klaster. Yang terakhir ini adalah jumlah kuadrat dalam "
+"klaster dibagi dengan jumlah total dari berbagai klaster. Output ini "
+"ditampilkan secara default."
 
 msgctxt "ClusterInfo|"
 msgid "Within sum of squares"
-msgstr ""
+msgstr "Dalam jumlah kuadrat"
 
 msgctxt "ClusterInfo|"
 msgid ""
 "Adds a row with the within sum of squares of each cluster to the table. This "
 "option is selected by default."
 msgstr ""
+"Menambahkan baris dengan jumlah kuadrat dalam setiap klaster ke tabel. Opsi "
+"ini dipilih secara default."
 
 msgctxt "ClusterInfo|"
 msgid "Silhouette score"
-msgstr ""
+msgstr "Skor siluet"
 
 msgctxt "ClusterInfo|"
 msgid "Adds a row with the silhouette score of each cluster to the table."
-msgstr ""
+msgstr "Menambahkan baris dengan skor siluet setiap klaster ke tabel."
 
 msgctxt "ClusterInfo|"
 msgid "Centers"
-msgstr ""
+msgstr "Pusat"
 
 msgctxt "ClusterInfo|"
 msgid ""
 "Adds a row with the center per feature of each cluster to the table. The "
 "center can be the mean, median or mode depending on the clustering algorithm."
 msgstr ""
+"Menambahkan baris dengan pusat per fitur dari setiap klaster ke tabel. Pusat "
+"dapat berupa rata-rata, median, atau modus, tergantung pada algoritme "
+"pengelompokan."
 
 msgctxt "ClusterInfo|"
 msgid "Between sum of squares"
-msgstr ""
+msgstr "Antara jumlah kuadrat"
 
 msgctxt "ClusterInfo|"
 msgid ""
 "Adds a note with the between sum of squares of the cluster model to the "
 "table."
 msgstr ""
+"Menambahkan catatan dengan jumlah kuadrat antara model klaster ke tabel."
 
 msgctxt "ClusterInfo|"
 msgid "Total sum of squares"
-msgstr ""
+msgstr "Jumlah total kuadrat"
 
 msgctxt "ClusterInfo|"
 msgid ""
 "Adds a note with the total sum of squares of the cluster model to the table."
 msgstr ""
+"Menambahkan catatan dengan jumlah total kuadrat dari model klaster ke tabel."
 
 msgctxt "ClusterMeans|"
 msgid "Shows a table containing the cluster means for each feature variable."
 msgstr ""
+"Menampilkan tabel yang berisi rata-rata klaster untuk setiap variabel fitur."
 
 msgctxt "ConfusionMatrix|"
 msgid "Confusion matrix"
-msgstr ""
+msgstr "Matriks kebingungan"
 
 msgctxt "ConfusionMatrix|"
 msgid ""
 "Displays a table that shows the observed classes against the predicted "
 "classes. Used to assess model accuracy."
 msgstr ""
+"Menampilkan tabel yang menunjukkan kelas yang diamati terhadap kelas yang "
+"diprediksi. Digunakan untuk menilai akurasi model."
 
 msgctxt "ConfusionMatrix|"
 msgid "Display proportions"
-msgstr ""
+msgstr "Menampilkan proporsi"
 
 msgctxt "ConfusionMatrix|"
 msgid "Displays proportions in the confusion matrix instead of counts."
-msgstr ""
+msgstr "Menampilkan proporsi dalam matriks kebingungan, bukan hitungan."
 
 msgctxt "ExplainPredictions|"
 msgid "Explain predictions"
-msgstr ""
+msgstr "Menjelaskan prediksi"
 
 msgctxt "ExplainPredictions|"
 msgid ""
 "Shows a decomposition of the predictions of the model into contributions "
 "that can be attributed to individual model features."
 msgstr ""
+"Menunjukkan dekomposisi prediksi model ke dalam kontribusi yang dapat "
+"dikaitkan dengan fitur model individual."
 
 msgctxt "ExplainPredictions|"
 msgid "Cases"
-msgstr ""
+msgstr "Kasus"
 
 msgctxt "ExplainPredictions|"
 msgid "The test set index of the first row to be displayed in the table."
 msgstr ""
+"Indeks set pengujian dari baris pertama yang akan ditampilkan dalam tabel."
 
 msgctxt "ExplainPredictions|"
 msgid "to"
-msgstr ""
+msgstr "untuk"
 
 msgctxt "ExplainPredictions|"
 msgid "The test set index of the last row to be displayed in the table."
 msgstr ""
+"Indeks set pengujian dari baris terakhir yang akan ditampilkan dalam tabel."
 
 msgctxt "FeatureImportance|"
 msgid "Feature importance"
-msgstr ""
+msgstr "kepentingan fitur"
 
 msgctxt "FeatureImportance|"
 msgid "Shows the available feature importance metrics for the fitted model."
 msgstr ""
+"Menunjukkan metrik kepentingan fitur yang tersedia untuk model yang dipasang."
 
 msgctxt "ModelPerformance|"
 msgid "Model performance"
-msgstr ""
+msgstr "Performa model"
 
 msgctxt "ModelPerformance|"
 msgid ""
@@ -1950,39 +2091,44 @@ msgstr ""
 
 msgctxt "ClusterDetermination|"
 msgid "Cluster Determination"
-msgstr ""
+msgstr "Penentuan Klaster"
 
 msgctxt "ClusterDetermination|"
 msgid "Choose how to determine the number of clusters in the model."
-msgstr ""
+msgstr "Pilih cara menentukan jumlah cluster dalam model."
 
 msgctxt "ClusterDetermination|"
 msgid "Fixed"
-msgstr ""
+msgstr "Tetap"
 
 msgctxt "ClusterDetermination|"
 msgid ""
 "Enables you to generate a fixed amount of clusters. This allows you to "
 "generate your own specified number of clusters, and thus, optimize manually."
 msgstr ""
+"Memungkinkan Anda menghasilkan jumlah kluster yang tetap. Hal ini "
+"memungkinkan Anda untuk menghasilkan jumlah cluster yang Anda tentukan "
+"sendiri, dan dengan demikian, mengoptimalkan secara manual."
 
 msgctxt "ClusterDetermination|"
 msgid "Clusters"
-msgstr ""
+msgstr "Kluster"
 
 msgctxt "ClusterDetermination|"
 msgid "The number of clusters to be fitted."
-msgstr ""
+msgstr "Jumlah kluster yang akan dipasang."
 
 msgctxt "ClusterDetermination|"
 msgid "Optimized according to"
-msgstr ""
+msgstr "Dioptimalkan menurut"
 
 msgctxt "ClusterDetermination|"
 msgid ""
 "Enables you to choose an optimization method. BIC optimization is set as "
 "default."
 msgstr ""
+"Memungkinkan Anda memilih metode pengoptimalan. Pengoptimalan BIC ditetapkan "
+"sebagai default."
 
 msgctxt "ClusterDetermination|"
 msgid ""
@@ -1995,20 +2141,30 @@ msgid ""
 "uses the similarity of observations within a cluster and their dissimilarity "
 "to other clusters for optimizing the clustering output."
 msgstr ""
+"Metode pengoptimalan. Pilihannya adalah AIC, BIC, dan siluet. AIC "
+"menggunakan jumlah kuadrat dalam (variasi dalam klaster), jumlah klaster "
+"yang dihasilkan, dan jumlah dimensi untuk mengoptimalkan output "
+"pengelompokan. BIC menggunakan jumlah kuadrat dalam (variasi dalam klaster), "
+"jumlah klaster yang dihasilkan, jumlah dimensi, dan ukuran sampel untuk "
+"mengoptimalkan output pengelompokan. Nilai silhouette menggunakan kemiripan "
+"pengamatan dalam sebuah cluster dan ketidakmiripan mereka dengan cluster "
+"lain untuk mengoptimalkan hasil pengelompokan."
 
 msgctxt "ClusterDetermination|"
 msgid "Max. clusters"
-msgstr ""
+msgstr "Maks. kluster"
 
 msgctxt "ClusterDetermination|"
 msgid ""
 "Sets the maximum number of possible clusters to be generated. At default, "
 "this is set to 10."
 msgstr ""
+"Mengatur jumlah maksimum kluster yang mungkin dibuat. Secara default, ini "
+"diatur ke 10."
 
 msgctxt "DataSplit|"
 msgid "Choose how to create the test set."
-msgstr ""
+msgstr "Pilih cara membuat set pengujian."
 
 msgctxt "DataSplit|"
 msgid ""
@@ -2016,19 +2172,25 @@ msgid ""
 "error. Generates an internal indicator variable that indicates whether the "
 "observation is included (1) or excluded (0) from the test set."
 msgstr ""
+"Pilih persentase untuk mengambil sampel secara acak dari data Anda untuk "
+"mendapatkan kesalahan prediksi. Menghasilkan variabel indikator internal "
+"yang mengindikasikan apakah pengamatan termasuk (1) atau tidak termasuk (0) "
+"dalam set pengujian."
 
 msgctxt "DataSplit|"
 msgid "The percentage of observations to use for the test set."
-msgstr ""
+msgstr "Persentase pengamatan yang akan digunakan untuk set pengujian."
 
 msgctxt "DataSplit|"
 msgid ""
 "Add the generated test set indicator from the option above to your data set."
 msgstr ""
+"Tambahkan indikator set pengujian yang dihasilkan dari opsi di atas ke set "
+"data Anda."
 
 msgctxt "DataSplit|"
 msgid "The column name for the generated test set indicator."
-msgstr ""
+msgstr "Nama kolom untuk indikator set pengujian yang dihasilkan."
 
 msgctxt "DataSplit|"
 msgid ""
@@ -2038,36 +2200,43 @@ msgid ""
 "a training (and validation if requested) set (0), and a test set (1) "
 "according to your indicator."
 msgstr ""
+"Gunakan variabel indikator untuk memilih data untuk set pengujian. Indikator "
+"ini harus berupa kolom dalam data Anda yang hanya terdiri dari 0 (tidak "
+"termasuk dalam set pengujian) dan 1 (termasuk dalam set pengujian). Data "
+"kemudian akan dibagi menjadi set pelatihan (dan validasi jika diminta) (0), "
+"dan set tes (1) sesuai dengan indikator Anda."
 
 msgctxt "DataSplit|"
 msgid "The variable in the data set that is used as the test set indicator."
-msgstr ""
+msgstr "Variabel dalam set data yang digunakan sebagai indikator set pengujian."
 
 msgctxt "DataSplit|"
 msgid "Choose how to create the validation set."
-msgstr ""
+msgstr "Pilih cara membuat set validasi."
 
 msgctxt "DataSplit|"
 msgid ""
 "Randomly sample a percentage from the remaining training data (after "
 "selecting the test set)."
 msgstr ""
+"Secara acak mengambil sampel persentase dari data pelatihan yang tersisa ("
+"setelah memilih set pengujian)."
 
 msgctxt "DataSplit|"
 msgid "The percentage of observations to use for the validation set."
-msgstr ""
+msgstr "Persentase pengamatan yang akan digunakan untuk set validasi."
 
 msgctxt "DataSplit|"
 msgid "Partition the remaining data in *k* parts."
-msgstr ""
+msgstr "Pisahkan data yang tersisa menjadi beberapa bagian *k*."
 
 msgctxt "DataSplit|"
 msgid "The number of folds to be used."
-msgstr ""
+msgstr "Jumlah lipatan yang akan digunakan."
 
 msgctxt "DataSplit|"
 msgid "Partition the remaining data in *n* parts."
-msgstr ""
+msgstr "Pisahkan data yang tersisa dalam *n* bagian."
 
 msgctxt "ExportResults|"
 msgid ""
@@ -2075,22 +2244,25 @@ msgid ""
 "result. This gives you the option to inspect, cluster, or predict the "
 "generated values."
 msgstr ""
+"Menghasilkan kolom baru dalam set data Anda dengan nilai hasil regresi Anda. "
+"Hal ini memberikan Anda opsi untuk memeriksa, mengelompokkan, atau "
+"memprediksi nilai yang dihasilkan."
 
 msgctxt "ExportResults|"
 msgid "The column name for the predicted values."
-msgstr ""
+msgstr "Nama kolom untuk nilai yang diprediksi."
 
 msgctxt "ExportResults|"
 msgid "The file path for the saved model."
-msgstr ""
+msgstr "Jalur file untuk model yang disimpan."
 
 msgctxt "ExportResults|"
 msgid "When clicked, the model is exported to the specified file path."
-msgstr ""
+msgstr "Apabila diklik, model diekspor ke jalur file yang ditentukan."
 
 msgctxt "ScaleVariables|"
 msgid "Scale features"
-msgstr ""
+msgstr "Fitur skala"
 
 msgctxt "ScaleVariables|"
 msgid ""
@@ -2100,6 +2272,11 @@ msgid ""
 "the Z-score standardization of a mean of 0 and a standard deviation of 1. "
 "This option is selected by default."
 msgstr ""
+"Menstandarkan fitur kontinu dalam kumpulan data. Standarisasi memastikan "
+"bahwa nilai fitur dari rentang skala yang berbeda masuk ke dalam skala "
+"tertentu yang serupa. Hasilnya, standarisasi memberikan stabilitas numerik. "
+"JASP menggunakan standarisasi Z-score dengan nilai rata-rata 0 dan deviasi "
+"standar 1. Opsi ini dipilih secara default."
 
 msgctxt "SetSeed|"
 msgid "Set seed"
@@ -2118,49 +2295,55 @@ msgstr ""
 
 msgctxt "VariablesFormClassification|"
 msgid "Target"
-msgstr ""
+msgstr "Sasaran"
 
 msgctxt "VariablesFormClassification|"
 msgid "In this box, the variable that needs to be predicted should be entered."
-msgstr ""
+msgstr "Di dalam kotak ini, variabel yang perlu diprediksi harus dimasukkan."
 
 msgctxt "VariablesFormClassification|"
 msgid "Features"
-msgstr ""
+msgstr "Fitur"
 
 msgctxt "VariablesFormClassification|"
 msgid ""
 "In this box, the variables that provide information about the target "
 "variable should be entered."
 msgstr ""
+"Pada kotak ini, variabel-variabel yang memberikan informasi mengenai "
+"variabel sasaran harus dimasukkan."
 
 msgctxt "VariablesFormClustering|"
 msgid "Features"
-msgstr ""
+msgstr "Fitur"
 
 msgctxt "VariablesFormClustering|"
 msgid ""
 "In this box, the variables are need to be considered by the clustering "
 "algorithm should be entered."
 msgstr ""
+"Pada kotak ini, variabel-variabel yang perlu dipertimbangkan oleh algoritma "
+"pengelompokan harus dimasukkan."
 
 msgctxt "VariablesFormRegression|"
 msgid "Target"
-msgstr ""
+msgstr "Sasaran"
 
 msgctxt "VariablesFormRegression|"
 msgid "In this box, the variable that needs to be predicted should be entered."
-msgstr ""
+msgstr "Di dalam kotak ini, variabel yang perlu diprediksi harus dimasukkan."
 
 msgctxt "VariablesFormRegression|"
 msgid "Features"
-msgstr ""
+msgstr "Fitur"
 
 msgctxt "VariablesFormRegression|"
 msgid ""
 "In this box, the variables that provide information about the target "
 "variable should be entered."
 msgstr ""
+"Pada kotak ini, variabel-variabel yang memberikan informasi mengenai "
+"variabel target harus dimasukkan."
 
 msgctxt "mlClassificationBoosting|"
 msgid ""
@@ -2173,6 +2356,14 @@ msgid ""
 "- The target variable is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Boosting bekerja dengan menambahkan fitur secara berurutan ke dalam ansambel "
+"pohon keputusan, masing-masing fitur mengoreksi fitur sebelumnya. Namun, "
+"alih-alih mengubah bobot untuk setiap observasi yang diklasifikasikan secara "
+"salah pada setiap iterasi, metode Boosting mencoba menyesuaikan fitur baru "
+"dengan sisa kesalahan yang dibuat oleh fitur sebelumnya.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlClassificationDecisionTree|"
 msgid ""
@@ -2184,6 +2375,13 @@ msgid ""
 "- The target is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Decision Trees adalah algoritma pembelajaran terawasi yang menggunakan pohon "
+"keputusan sebagai model prediktif untuk beralih dari pengamatan tentang "
+"sebuah item (direpresentasikan di akar pohon) ke kesimpulan tentang nilai "
+"target item tersebut (direpresentasikan di titik akhir pohon).\n"
+"### Asumsi\n"
+"- Target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlClassificationKnn|"
 msgid ""
@@ -2196,6 +2394,14 @@ msgid ""
 "- The target is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"K-nearest neighbors adalah metode klasifikasi yang melihat *k* jumlah "
+"pengamatan fitur yang paling mirip dengan pengamatan baru untuk membuat "
+"prediksi penetapan kelasnya. Jumlah tetangga terdekat secara intrinsik "
+"terkait dengan kompleksitas model, karena jumlah yang kecil meningkatkan "
+"fleksibilitas model.\n"
+"### Asumsi\n"
+"- Target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlClassificationLda|"
 msgid ""
@@ -2214,10 +2420,23 @@ msgid ""
 "- Multicollinearity: The classes should not correlate within each other, can "
 "be checked with the corresponding table."
 msgstr ""
+"Linear Discriminant Analysis (LDA) adalah metode klasifikasi yang bertujuan "
+"untuk menemukan *p - 1* komponen yang membedakan dengan baik antara kelas-"
+"kelas dalam variabel target. LDA adalah pengklasifikasi linier, yang berarti "
+"bahwa batas keputusan antara kelas-kelas adalah linier.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal.\n"
+"- Kesetaraan rata-rata kelas: Rata-rata kelas harus sama, dapat diperiksa "
+"dengan tabel yang sesuai.\n"
+"- Kesetaraan matriks kovarians: Matriks kovarians harus sama, dapat "
+"diperiksa dengan tabel yang sesuai.\n"
+"- Multikolinearitas: Kelas-kelas tidak boleh berkorelasi satu sama lain, "
+"dapat diperiksa dengan tabel yang sesuai."
 
 msgctxt "mlClassificationLda|"
 msgid "Multivariate normality"
-msgstr ""
+msgstr "Normalitas multivariat"
 
 msgctxt "mlClassificationNeuralNetwork|"
 msgid ""
@@ -2232,6 +2451,17 @@ msgid ""
 "- The target is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous variables."
 msgstr ""
+"Jaringan saraf feedforward adalah algoritme prediktif yang terinspirasi oleh "
+"jaringan saraf biologis yang membentuk otak. Sebuah neuron (simpul) yang "
+"menerima sinyal kemudian memprosesnya dan dapat mengirim sinyal ke neuron "
+"yang terhubung dengannya. Sinyal pada sebuah node adalah bilangan real, dan "
+"output dari setiap node dihitung dengan mengirimkan sinyal melalui fungsi "
+"aktivasi. Jumlah lapisan dan node dalam jaringan secara intrinsik terkait "
+"dengan kompleksitas model, karena jumlah yang tinggi meningkatkan "
+"fleksibilitas model.\n"
+"### Asumsi\n"
+"- Target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu."
 
 msgctxt "mlClassificationRandomForest|"
 msgid ""
@@ -2244,6 +2474,13 @@ msgid ""
 "- The target variable is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Random Forest adalah metode klasifikasi yang menciptakan sekumpulan pohon "
+"keputusan yang terdiri dari sejumlah besar pohon individu yang beroperasi "
+"sebagai ansambel. Setiap pohon individu dalam random forest menghasilkan "
+"prediksi kelas dan kelas dengan suara terbanyak menjadi prediksi model.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlClassificationSvm|"
 msgid ""
@@ -2256,6 +2493,14 @@ msgid ""
 "- The target is a nominal or ordinal variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Support Vector Machines adalah algoritme pembelajaran terawasi yang "
+"memetakan contoh-contoh pelatihan ke titik-titik dalam ruang untuk "
+"memaksimalkan lebar kesenjangan antara dua kategori. Contoh-contoh baru "
+"kemudian dipetakan ke dalam ruang yang sama dan diprediksi masuk ke dalam "
+"kategori berdasarkan sisi mana dari kesenjangan tersebut.\n"
+"### Asumsi\n"
+"- Target adalah variabel nominal atau ordinal.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlClusteringDensityBased|"
 msgid ""
@@ -2273,6 +2518,20 @@ msgid ""
 "- The data consists of continuous variables.\n"
 "- (Normally distributed data aids the clustering process)."
 msgstr ""
+"Pengelompokan berbasis kepadatan adalah metode pengelompokan lunak di mana "
+"cluster dibangun sebagai kumpulan titik maksimum yang terhubung ke titik-"
+"titik yang kepadatannya melebihi ambang batas tertentu. Kepadatan dihasilkan "
+"oleh konsep bahwa untuk setiap titik dalam sebuah cluster, lingkungan dalam "
+"radius tertentu harus mengandung setidaknya jumlah minimum titik, yang "
+"menghasilkan kepadatan lingkungan tersebut melebihi ambang batas tertentu. "
+"Cluster berbasis kepadatan dikenali dari titik-titik yang memiliki kepadatan "
+"yang lebih tinggi daripada titik-titik di luar cluster. Kumpulan semua titik "
+"dengan kepadatan tinggi disebut tingkat kepadatan. Titik-titik yang tidak "
+"melebihi tingkat kepadatan diidentifikasi sebagai pencilan. Tingkat "
+"kepadatan mempengaruhi jumlah cluster yang dihasilkan.\n"
+"### Asumsi\n"
+"- Data terdiri dari variabel kontinu.\n"
+"- (Data yang terdistribusi secara normal akan membantu proses pengelompokan)."
 
 msgctxt "mlClusteringFuzzyCMeans|"
 msgid ""
@@ -2286,6 +2545,15 @@ msgid ""
 "- The data consists of continuous variables.\n"
 "- (Normally distributed data aids the clustering process)."
 msgstr ""
+"Fuzzy c-means clustering adalah metode soft partitioning yang memberikan "
+"output yang berisi derajat asosiasi untuk setiap observasi ke setiap "
+"cluster. Hal ini memungkinkan observasi data untuk ditugaskan sebagian ke "
+"beberapa klaster dan memberikan tingkat kepercayaan tentang keanggotaan "
+"klaster. Pendekatan Fuzzy c-means sangat mirip dengan k-means clustering, "
+"selain dari pendekatannya yang lebih lunak.\n"
+"### Asumsi-asumsi\n"
+"- Data terdiri dari variabel kontinu.\n"
+"- (Data yang terdistribusi secara normal akan membantu proses pengelompokan)."
 
 msgctxt "mlClusteringHierarchical|"
 msgid ""
@@ -2298,6 +2566,14 @@ msgid ""
 "- The data consists of continuous variables.\n"
 "- (Normally distributed data aids the clustering process)."
 msgstr ""
+"Hierarchical clustering adalah algoritma hard partitioning yang bertujuan "
+"untuk mempartisi data ke dalam beberapa cluster, di mana setiap observasi "
+"hanya menjadi bagian dari satu kelompok. Data dibagi sedemikian rupa "
+"sehingga tingkat kemiripan antara dua pengamatan data adalah maksimal jika "
+"mereka termasuk dalam kelompok yang sama dan minimal jika tidak.\n"
+"### Asumsi\n"
+"- Data terdiri dari variabel kontinu.\n"
+"- (Data yang terdistribusi secara normal akan membantu proses pengelompokan)."
 
 msgctxt "mlClusteringKMeans|"
 msgid ""
@@ -2310,6 +2586,15 @@ msgid ""
 "- The data consists of continuous variables.\n"
 "- (Normally distributed data aids the clustering process)."
 msgstr ""
+"Metode pengelompokan berbasis lingkungan adalah sekumpulan algoritma hard "
+"partitioning yang bertujuan untuk mempartisi data ke dalam beberapa cluster, "
+"di mana setiap observasi hanya menjadi bagian dari satu kelompok. Data "
+"dibagi sedemikian rupa sehingga tingkat kemiripan antara dua pengamatan data "
+"adalah maksimal jika mereka termasuk dalam kelompok yang sama dan minimal "
+"jika tidak.\n"
+"### Asumsi\n"
+"- Data terdiri dari variabel kontinu.\n"
+"- (Data yang terdistribusi secara normal akan membantu proses pengelompokan)."
 
 msgctxt "mlClusteringRandomForest|"
 msgid ""
@@ -2324,24 +2609,36 @@ msgid ""
 "- The data consists of continuous variables.\n"
 "- (Normally distributed data aids the clustering process)."
 msgstr ""
+"Clustering Random Forest adalah algoritma hard partitioning yang bertujuan "
+"untuk mempartisi data ke dalam beberapa cluster, di mana setiap observasi "
+"hanya menjadi bagian dari satu kelompok. Metode pengelompokan ini "
+"menggunakan algoritma Random Forest dengan cara yang tidak terawasi, dengan "
+"variabel hasil 'y' diatur ke NULL. Algoritma Random Forest menghasilkan "
+"matriks kedekatan yang memberikan estimasi jarak antar observasi berdasarkan "
+"frekuensi observasi yang berakhir pada leaf node yang sama.\n"
+"### Asumsi-asumsi\n"
+"- Data terdiri dari variabel-variabel kontinu.\n"
+"- (Data yang terdistribusi normal akan membantu proses pengelompokan)."
 
 msgctxt "mlPrediction|"
 msgid ""
 "The prediction analysis enables you to load a trained machine learning model "
 "and apply it to new data."
 msgstr ""
+"Analisis prediksi memungkinkan Anda memuat model pembelajaran mesin yang "
+"telah dilatih dan menerapkannya pada data baru."
 
 msgctxt "mlPrediction|"
 msgid "Cases"
-msgstr ""
+msgstr "Kasus"
 
 msgctxt "mlPrediction|"
 msgid "Add features"
-msgstr ""
+msgstr "Menambahkan fitur"
 
 msgctxt "mlPrediction|"
 msgid "Explain predictions"
-msgstr ""
+msgstr "Menjelaskan prediksi"
 
 msgctxt "mlRegressionBoosting|"
 msgid ""
@@ -2352,10 +2649,17 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Boosting bekerja dengan menambahkan fitur secara berurutan ke dalam ansambel "
+"pohon keputusan, masing-masing fitur mengoreksi fitur sebelumnya. Boosting "
+"mencoba menyesuaikan fitur baru dengan sisa kesalahan yang dibuat oleh fitur "
+"sebelumnya.\n"
+"### Asumsi-asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlRegressionBoosting|"
 msgid "The loss function used."
-msgstr ""
+msgstr "Fungsi kehilangan yang digunakan."
 
 msgctxt "mlRegressionDecisionTree|"
 msgid ""
@@ -2367,6 +2671,13 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Decision Trees adalah algoritma pembelajaran terawasi yang menggunakan pohon "
+"keputusan sebagai model prediktif untuk beralih dari pengamatan tentang "
+"sebuah item (direpresentasikan di akar pohon) ke kesimpulan tentang nilai "
+"target item tersebut (direpresentasikan di titik akhir pohon).\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlRegressionKnn|"
 msgid ""
@@ -2379,28 +2690,39 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"K-nearest neighbors adalah metode regresi yang melihat *k* jumlah pengamatan "
+"fitur yang paling mirip dengan pengamatan baru untuk membuat prediksi "
+"nilainya. Jumlah tetangga terdekat secara intrinsik terkait dengan "
+"kompleksitas model, karena jumlah yang kecil meningkatkan fleksibilitas "
+"model.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlRegressionLinear|"
 msgid ""
 "Linear regression allows the user to model a linear relationship between one "
 "or more features (predictors) and a continuous dependent (target) variable."
 msgstr ""
+"Regresi linier memungkinkan pengguna untuk memodelkan hubungan linier antara "
+"satu atau lebih fitur (prediktor) dan variabel dependen (target) yang "
+"kontinu."
 
 msgctxt "mlRegressionLinear|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlRegressionLinear|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlRegressionLinear|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlRegressionLinear|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlRegressionNeuralNetwork|"
 msgid ""
@@ -2415,6 +2737,17 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous."
 msgstr ""
+"Jaringan saraf feedforward adalah algoritme prediktif yang terinspirasi oleh "
+"jaringan saraf biologis yang membentuk otak. Sebuah neuron (simpul) yang "
+"menerima sinyal kemudian memprosesnya dan dapat mengirim sinyal ke neuron "
+"yang terhubung dengannya. Sinyal pada sebuah node adalah bilangan real, dan "
+"output dari setiap node dihitung dengan mengirimkan sinyal melalui fungsi "
+"aktivasi. Jumlah lapisan dan node dalam jaringan secara intrinsik terkait "
+"dengan kompleksitas model, karena jumlah yang tinggi meningkatkan "
+"fleksibilitas model.\n"
+"### Asumsi-asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu."
 
 msgctxt "mlRegressionRandomForest|"
 msgid ""
@@ -2425,6 +2758,12 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Random Forest adalah sebuah metode regresi yang menciptakan sekumpulan pohon "
+"keputusan yang terdiri dari sejumlah besar pohon individu yang beroperasi "
+"sebagai sebuah ensemble.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlRegressionRegularized|"
 msgid ""
@@ -2436,6 +2775,13 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variables."
 msgstr ""
+"Regresi linier teregresi adalah adaptasi dari regresi linier di mana "
+"koefisien menyusut menuju 0. Hal ini dilakukan dengan menerapkan penalti ("
+"misalnya, punggungan, laso, atau jaring elastis). Parameter λ mengontrol "
+"sejauh mana parameter menyusut.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal."
 
 msgctxt "mlRegressionSvm|"
 msgid ""
@@ -2448,6 +2794,14 @@ msgid ""
 "- The target variable is a continuous variable.\n"
 "- The feature variables consist of continuous, nominal, or ordinal variable"
 msgstr ""
+"Support Vector Machines adalah algoritme pembelajaran terawasi yang "
+"memetakan contoh-contoh pelatihan ke titik-titik dalam ruang untuk "
+"memaksimalkan lebar kesenjangan antara dua kategori. Contoh-contoh baru "
+"kemudian dipetakan ke dalam ruang yang sama dan diprediksi masuk ke dalam "
+"kategori berdasarkan sisi mana dari kesenjangan tersebut.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel kontinu.\n"
+"- Variabel fitur terdiri dari variabel kontinu, nominal, atau ordinal"
 
 msgctxt "Description|"
 msgid "Naive Bayes"
@@ -2464,32 +2818,40 @@ msgstr ""
 msgctxt "ModelOptimization|"
 msgid "Enables you to use a user-specified complexity penalty."
 msgstr ""
+"Memungkinkan Anda menggunakan penalti kompleksitas yang ditentukan pengguna."
 
 msgctxt "ModelOptimization|"
 msgid "Complexity penalty"
-msgstr ""
+msgstr "Penalti kompleksitas"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "The complexity penalty to be used. Any split that does not decrease the "
 "overall lack of fit by a factor of this parameter is not attempted."
 msgstr ""
+"Penalti kompleksitas yang akan digunakan. Setiap pemisahan yang tidak "
+"mengurangi keseluruhan ketidaksesuaian dengan faktor parameter ini tidak "
+"akan dicoba."
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Enables you to optimize the prediction error on a validation data set with "
 "respect to the complexity penalty."
 msgstr ""
+"Memungkinkan Anda untuk mengoptimalkan kesalahan prediksi pada kumpulan data "
+"validasi sehubungan dengan penalti kompleksitas."
 
 msgctxt "ModelOptimization|"
 msgid "Max. complexity penalty"
-msgstr ""
+msgstr "Maks. penalti kompleksitas"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Sets the maximum value of the complexity penalty to be considered. At "
 "default, this is set to 1."
 msgstr ""
+"Menetapkan nilai maksimum penalti kompleksitas yang akan dipertimbangkan. "
+"Secara default, ini diatur ke 1."
 
 msgctxt "OptimPlot|"
 msgid ""
@@ -2499,34 +2861,44 @@ msgid ""
 "accuracy of the model. Accuracy is assessed for the training (and "
 "validation) set."
 msgstr ""
+"Untuk regresi, memplot penalti kompleksitas terhadap MSE model. Akurasi "
+"dinilai untuk set pelatihan (dan validasi). Untuk klasifikasi, memplot "
+"penalti kompleksitas terhadap akurasi klasifikasi model. Akurasi dinilai "
+"untuk set pelatihan (dan validasi)."
 
 msgctxt "ModelOptimization|"
 msgid "Costs of Contraints Violation"
-msgstr ""
+msgstr "Biaya Pelanggaran terhadap Kendala"
 
 msgctxt "ModelOptimization|"
 msgid "Enables you to use a user-specified cost of constraints violation."
 msgstr ""
+"Memungkinkan Anda menggunakan biaya pelanggaran batasan yang ditentukan "
+"pengguna."
 
 msgctxt "ModelOptimization|"
 msgid "Violation cost"
-msgstr ""
+msgstr "Biaya pelanggaran"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Enables you to optimize the prediction error on a validation data set with "
 "respect to the cost of constraints violation."
 msgstr ""
+"Memungkinkan Anda untuk mengoptimalkan kesalahan prediksi pada kumpulan data "
+"validasi sehubungan dengan biaya pelanggaran batasan."
 
 msgctxt "ModelOptimization|"
 msgid "Max. violation cost"
-msgstr ""
+msgstr "Maks. biaya pelanggaran"
 
 msgctxt "ModelOptimization|"
 msgid ""
 "Sets the maximum value of the cost of constraints violation to be "
 "considered. At default, this is set to 5."
 msgstr ""
+"Mengatur nilai maksimum dari biaya pelanggaran batasan yang akan "
+"dipertimbangkan. Secara default, ini diatur ke 5."
 
 msgctxt "OptimPlot|"
 msgid ""
@@ -2536,6 +2908,10 @@ msgid ""
 "classification accuracy of the model. Accuracy is assessed for the training "
 "(and validation) set."
 msgstr ""
+"Untuk regresi, plot biaya pelanggaran batasan terhadap MSE model. Akurasi "
+"dinilai untuk set pelatihan (dan validasi). Untuk klasifikasi, memplot biaya "
+"pelanggaran batasan terhadap akurasi klasifikasi model. Akurasi dinilai "
+"untuk set pelatihan (dan validasi)."
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid ""
@@ -2547,14 +2923,21 @@ msgid ""
 "- The features are independent.\n"
 "- The features are normally distributed given the target class."
 msgstr ""
+"Naive Bayes menghitung probabilitas posterior bersyarat dari variabel kelas "
+"kategorikal yang diberikan variabel prediktor independen menggunakan aturan "
+"Bayes.\n"
+"### Asumsi\n"
+"- Variabel target adalah variabel nominal atau ordinal.\n"
+"- Fitur-fitur bersifat independen.\n"
+"- Fitur-fitur terdistribusi secara normal berdasarkan kelas target."
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Tables"
-msgstr ""
+msgstr "Tabel"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Posterior statistics"
-msgstr ""
+msgstr "Statistik posterior"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid ""
@@ -2563,34 +2946,40 @@ msgid ""
 "class. For categorical features, the table displays the conditional "
 "probabilities given the target class."
 msgstr ""
+"Menampilkan tabel dengan statistik posterior. Untuk fitur numerik, tabel "
+"berisi rata-rata dan deviasi standar fitur yang diberikan kelas target. "
+"Untuk fitur kategorik, tabel menampilkan probabilitas bersyarat yang "
+"diberikan kelas target."
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Plots"
-msgstr ""
+msgstr "Plot"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Training Parameters"
-msgstr ""
+msgstr "Parameter Pelatihan"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Algorithmic Settings"
-msgstr ""
+msgstr "Pengaturan Algoritmik"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid "Smoothing parameter"
-msgstr ""
+msgstr "Parameter penghalusan"
 
 msgctxt "mlClassificationNaiveBayes|"
 msgid ""
 "A positive double controlling the amount of Laplace smoothing applied. The "
 "default (0) disables Laplace smoothing alltogether."
 msgstr ""
+"Ganda positif mengontrol jumlah penghalusan Laplace yang diterapkan. Default "
+"(0) menonaktifkan penghalusan Laplace sama sekali."
 
 msgctxt "FeatureImportance|"
 msgid "Permutations"
-msgstr ""
+msgstr "Permutasi,"
 
 msgctxt "FeatureImportance|"
 msgid ""
 "Sets the number of permutations on which the mean dropout loss is based."
-msgstr ""
+msgstr "Mengatur jumlah permutasi yang menjadi dasar rata-rata kehilangan."