PENERAPAN METODE DECISION TREE C4.5 DALAM MEMPREDIKSI KELANCARAN PEMBAYARAN KREDIT DI BPR WAHANA BERSAMA KPUM

Abstract

BPR Wahana Bersama KPUM is a lending company. Delay in credit payments is a problem that occurs in credit companies. Customers who don't pay on time can have a bad impact on their credit history. To assess customer profitability, a system is needed that can predict the smoothness of future credit payments in order to assess whether customers are profitable or not. The author uses the Decision Tree C4.5 method in which the method looks for similarities between classes or groups in the data. In this study, the data used is customer data, with training data from 2017-2020 and testing data from 2021. The existence of this system can help BPR Wahana Bersama KPUM in predicting the smoothness of credit payments in the future so that there will be no credit payment jams by customers. , this is proven by the acquisition of the accuracy value using the confusion matrix model reaching 84.18%.