Aplikasi Data Mining dengan Menggunakan Metode Naive Bayes untuk Prediksi Penentuan Resiko Kredit pada Koperasi Sido Makmur

Abstract Cooperation is are legal entities that serve savings and loan services. Sido Makmur Cooperation is a financial institution that serves savings and loan services. In granting cooperation of Sido Makmur is still using the manual method by looking at the record of the ledger that is in the cooperation. Before the cooperation gives credit to the customer, the cooperation must conduct a survey to find out whether the loan applicant is eligible or not eligible for credit. Surveys must be carried out carefully to avoid the occurrence of credit less smoothly. Decision support is needed to help the cooperation in predicting credit applicants. So a system is created that can classify which factors have the most influence on the level of credit payments in cooperation. So from that this study uses Naïve Bayes to produce easy decisions, and has the value of accuracy obtained. In the application there is a feature that can be used to make decisions for customers who will apply for credit at a cooperation. Blackbox testing on the application can run well as well as testing algorithms that have been running well on the application made. The results of this study showed that the average value of Accuracy testing reached 75%. Keywords: Naïve Bayes, Cooperation, Credit, Prediction, Data Mining