Default Risk Prediction Using Decision Tree Study Case of Home Credit - Adipurwa Mahandiri, Dewa Nyoman Agung; Muliantara, Agus (JELIKU (Jurnal Elektronik Ilmu Komputer Udayana); Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024, 2024)
Consuming loans with any service has become a trend in modern society. However, that trend gives some risk for the loan company such as Home Credit. Home Credit needs to create an automation analytic for predicting customers that might be default in future. So, we build a machine learning model using the Decision Tree algorithm to resolve that risk. The Decision Tree model can give mean score 85% accuracy ,  91% precision , and 92% recall score  for Home Credit study case.