Debtors Prospective Assessment Application using Naive Bayes at Mitra Sejahtera Cooperative

Utilization of historical data into new knowledge can increase added value for its users, including Mitra Setia Cooperative (KMS) which has debtor that is not utilized. “Not Paid Off” potentioal debtors cannot be detected as early possible. In this study using the Naive Bayes algorithm in classifying feasibility prospective based on classification "Paid Off" and "Not parameter Age, Sex, Amount Loan, Occupation, Income, Repayment Period. The research stages consist (1) Research Initiation, (2) Data Selection, (3) Preprocessing, (4) System Design, (5) Program Implementation (6) Testing. purpose to minimize bad loans by implementing method application assessment debtors. final result a at Sejahtera with an accuracy rate 86%