ANALISIS KELAYAKAN PEMBERIAN KREDIT KOPERASI DENGAN METODE DATA MINING DECISION TREE

Abstract

Savings and loan cooperatives provide credit to members with certain criteria. This study was conducted to analyze the feasibility of providing credit to members of savings and loan cooperatives. In developing their business cooperatives have problems choosing employees who are eligible or not in providing savings and loan cooperatives so that the cooperative's financial cycle can run in an orderly and smooth manner. The attributes used as test data are discipline, class, age, years of service, and other income. The research uses the decision tree algorithm C4.5 data mining method with rapidminer tools on the data of prospective cooperative creditors. The results obtained are 94.27% accuracy, 100% precision, and 89.29% recall.