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All Journal Tsabit
Surya Lesmana
Universitas Muhammadiyah Sumatera Utara
Computer Science & IT

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Implementation of the Naïve Bayes Algorithm in Credit Card Approval Classification at Bank Central Asia (BCA) Surya Lesmana; Firahmi Rizky
Tsabit Journal of Computer Science Vol. 3 No. 1 (2026): June Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/tsabit80

Abstract

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.
Co-Authors Firahmi Rizky