Sistem Klasifikasi Kelayakan Debitur Lembaga Perkreditan Desa Menggunakan Algoritma C4.5 dan Bagging

Abstract

LPD Penarukan is one of the financial institutions that provides credit loans to people in the Penarukan traditional village area, Bali Province. This study aims to assist credit officers in classifying loans submitted by prospective debtors based on analysis of character, capacity, capital, collateral, and economic conditions by developing a credit classification system with a case study on LPD Penarukan using the C4.5 algorithm with bagging technique. Based on the results of research and testing that have been carried out, the system built is able to carry out the process of classifying credit data indicated by the results of usability testing giving the learnability component has an average value of 78.2%, the memorability component has an average value of 74.07%. The efficiency component gets an average value of 83.70%, the error component gets an average of 82.22%, the satisfaction component gets an average value of 83.89%. Tests were also carried out by calculating the accuracy and F1 score using the C4.5 algorithm with the bagging technique which resulted in an accuracy value of 81.87% and an F1 score of 89.62%.