Comparison of the Naïve Bayes Classifier and Decision Tree J48 for Credit Classification of Bank Customers

The bank conducts an analysis or survey in the credit system to determine whether customer is eligible receive credit. With a case study of Bank BJB debtor data December 2021, classification was carried out by forming model using Naïve Bayes Classifier and Decision Tree J48. Thus it expected minimize occurrence bad loans. are divided into several categories: debtors with good, substandard, doubtful, 10-fold cross-validation model, where results obtained from both tests, highest accuracy value J48 78.26%. While has lower level accuracy, prediction tend be better than can predict all classes most influential variable classifying loan term.