<![CDATA[NSC Finance is a service business that provides loans to the public to meet their needs. However, NSC Finance does not use customer data to obtain necessary information. This research classifies customer data to gain information about promising customers, considered customers, and unpromising customers to loan re-offer. This study compares Naïve Bayes and C4.5 to help customer classification systems be more accurate by measuring accuracy using recall precision. These methods' comparative analyses are to investigate which methods have the highest classification accuracy. Therefore, the company can discover the highest accuracy rate of the classification results of these two methods. Results revealed that the classification patterns of 80 training data and 20 test data make it possible that data still have classification differences from the original data. Methods comparison indicated that the Naïve Bayes classification is better, with 85% accuracy, 94.44% precision, and 89.47% recall.]]>
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