Aplikasi Asesmen Calon Debitur menggunakan Naive Bayes di Koperasi Mitra Sejahtera SMK Negeri 1 Kota Sukabumi

Abstract

Cooperatives have an important role in economic development in Indonesia. One of them is the Mitra Sejahtera Cooperative (KMS), which is located in Sukabumi - West Java. The problem that in KMS was the increase in bad credit during the 2015-2019 period which had an impact on decreasing cash circulation flow and income of the KMS. So that in this study focuses on making a prospective debtor assessment application by implementing the Naive Bayes algorithm to provide recommendations on the feasibility of prospective debtors who have the potential for bad credit or not. The training data used are 862 data with parameters of age, gender, loan amount, occupation, income and repayment period. The stages taken include: (1) Research Initiation, (2) Data Selection, (3) Data Pre Processing, (4) System Design, (5) System Implementation, and (6) Program Testing. In system design using structured design, while the implementation of the system uses Microsoft Visual Studio 2012 tools and MySQL database. The test results from the prospective debtor assessment application obtained an accuracy rate of 86%.