Analisis akurasi metode seleksi fitur gram-schmidt orthogonalization pada support vector machine untuk big data-studi kasus masalah prediksi klaim = Analyzing accuracy of feature selection method gram-schmidt orthogonalization for support vector machine on big data-a case study of claim prediction problem

Analisis akurasi Deep Neural Network (DNN) untuk big structured data studi kasus prediksi biaya kerugian pada asuransi kebakaran = Analyzing accuracy of Deep Neural Network (DNN) for big structured data a case study of loss cost prediction in insurance

Analisis akurasi model XGBoost untuk klasifikasi multikelas: studi kasus prediksi tingkat klaim risiko pemohon pada asuransi jiwa = Analyzing accuracy of XGBoost model for multiclass classification: a case study of the applicant level claim risk prediction for life insurance

Analisis akurasi metode support vector machine, random forest, dan logistic regression dalam mengklasifikasi data asuransi mobil dengan implementasi metode seleksi fitur one dimensional naive bayes classifier = Accuracy analysis of support vector machine, random forest, and logistic regression method in classifying car insurance data with one dimensional naive bayes classifier features selection implementation

Prediksi Distribusi Dosis pada Perencanaan IMRT Kasus Kanker Paru menggunakan model Random-Forest = Prediction of Dose Dostribution In Planning IMRT For Lung Cancer Using Random-Forest Model