Abstract
A cooperative is a financial institution located in each village. Cooperatives can provide solutions to the community when the community's economic needs are decreasing. One of the services provided by cooperatives to the community is credit loans. This research focuses on analyzing the suitability of prospective cooperative member creditors who are eligible for credit applications. This analysis requires attributes or variables that are suitable for use in the credit application process. The attributes used in this research are that prospective creditors must be of sufficient age, disciplined in the payment process according to the monthly due date, have income and have allowances. This research uses data mining techniques using the Naïve Bayes algorithm, and data processing uses the Rapidminer application. The results obtained were based on the results of processing 182 data, namely obtaining an accuracy value of 81.32%, precision of 89.36% and recall of 77.78%. In this case, credit worthiness analysis with four attributes using the Naïve Bayes algorithm is suitable for use with accurate and precise results.
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