Prediksi Kolektibilitas Kredit Anggota Dengan Algoritma C5.0 (Studi Kasus: Cu Damai Sejahtera Medan)

Abstract

CU Damai Sejahtera is one of the cooperatives that move in the business of saving and loan. This has the same role as other large financial institutions such as banks in improving the economy of the community, in particular, is a member of CU itself. As a financial institution, bad credit is a major problem that is very influential on the sustainability of a financial institution. loss of earnings and the threat of profitability is a matter of caution in lending. Credit collectibility as one form of classification will facilitate the classification of each member data based on supporting criteria. The result of a decision tree that produces information in the form of a rule, will facilitate the analysis and retrieval later. With decision tree using C5.0 algorithm is expected to process information digging faster and optimal with bigger data capacity, so that errors generated in decision making more minimized.