Prediction of Credit Card Using the Naïve Bayes Method and C4.5 Algorithm

Abstract

Prediction credit card submission is a system that is able to provide an assessment of alternatives in order to help credit card applicants in making decisions. Many methods can be used in building a prediction system for credit card submissions. This research will compare two methods in predicting credit card submission, namely the naïve bayes method and c4.5 algorithm, case study of Credit Card Submission Prediction, the results of the research are, knowing the level of accuracy of the two methods. Criteria that form the basis of decision making include age, sex, recent education, marital status, number of dependents, type of company, monthly income, and salary slip. The final result found that the naïve bayes method and the c4.5 algorithm are relatively the same.