INFORMATION SYSTEM DESIGN FOR SMOOTHNESS OF CREDIT PAYMENTS AT BANK DANAMON
Abstract
Application developers and users are key to the market impact on application development. In developing applications, it is necessary to predict applications in the market accurately, accurate prediction results are very important in showing the rating and making the right decisions in the selection of new prospective debtors. The tests carried out in this test use a dataset of credit customers from Bank Danamon. In this study, predictions of the smooth rate of credit payments will be made by combining the Naïve Bayes and K-Nearest Neighbor methods. Prediction of the smooth rate of credit payments using a combination of the Naïve Bayes algorithm and K-Nearest Neighbor is able to predict the smoothness of credit payments in the future, this can be seen from the prediction results obtained by 80%.
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References
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