ANALYSIS OF CREDIT FEASIBILITY USING THE DECISION TREE METHOD (Case Study at CP Rantepao Pawnshop)

Abstract

This study aims to analyze the feasibility of providing credit at Pegadaian CP Rantepao using the decision tree method. Quantitative research is the method used. The population in this study was 413 customer data, 100 of which were used as samples provided by Pegadaian CP Rantepao. The type of data used is secondary data, in the form of customer data registered at Pegadaian CP Rantepao. The data analysis used in this research is using Data Mining Clarification with the C4.5 Algorithm Method. The results showed that by using the Decision Tree method to determine customer status on CP Rantepao Pawnshop Customer data, it was able to classify or predict customer data into categories, namely current and bad using 5 attributes, namely gender, loan time, collateral, product type and installations. Based on tests that have been carried out using Confusion Matrix, the accuracy value is 75.71%.