Rahmat Budiarsa

Pembuatan Model Machine Learning untuk Klasifikasi Risiko Pinjaman Perbankan Menggunakan Random Forest dan XGboost

It is shown that XGBoost with preprocessing and the second hyperparameter tuning achieved the best performance, with an accuracy of 98%, precision of 97%, recall of 85%, and F1-score of 90%, outperforming Random Forest on the dataset used.