Rahmad Firdaus

Prediksi Keberhasilan Akademik Siswa Berbasis Fitur Kategorikal Na-tive dengan Explainable AI (SHAP) menggunakan CatBoost vs LightGBM

Prediction of students academic success is important to support decision-making in education. Educational datasets are generally dominated by categorical variables that require encoding before modeling, which may cause information loss and reduce accuracy. This study applies the CatBoost algorithm, which processes cate...