Implementation of the Naïve Bayes Algorithm in Credit Card Approval Classification at Bank Central Asia (BCA) - Surya Lesmana; Firahmi Rizky (Ilmu Bersama Center, 2026)
Credit card approval is a financial facility that allows a person or business entity to borrow money to purchase products and repay it within a mutually agreed time. Researchers used a credit card approval dataset (Clean Data) of 200 data with 6 atributes. In conducting the analysis, researchers used the WEKA tools. In this study the author wants to classify the data to predict whether or not it is appropriate to grant a credit card. The method used is the Naïve Bayes Algorithm method. In this study, the data was split by 60:40, 70:30, and 80:20. The author also obtained different accurasy result, namely in the Weka data Testing tool 20% using the use Training Set obtained the highest accuracy of 87.68% compared to the lowest accuracy in the 30% testing data using the use Training Set, which is 80.60% The Naïve Bayes Algorithm can be said to be one of the effective Algorithm both in the terms of calculations and final results where the test can be used as a basis for credit card approval.