Department of CSE, Gono Bishwabidyalay, University department in Bangladesh, Bangladesh.
Research Article
World Journal of Advanced Research and Reviews, 2023, 17(02), 839-843
Article DOI: 10.30574/wjarr.2023.17.2.0330
Received on 14 January 2023; revised on 25 February 2023; accepted on 28 February 2023
During the final two decades, the credit card framework has been broadly utilized as a component to drive the worldwide economy to develop significantly. A credit card supplier has issued millions of credit cards to its clients. Be that as it may, issuing credit cards to off-base clients can be a pivotal calculation of a monetary emergency. The objective of this paper is to mine useful data from the databases and apply data mining algorithms for processing credit card applications based on certain criteria. We have done the credit card application processing through k-clusters and decision trees, thus making the process easy and efficient. The processing takes place by considering the applicant's data in a day and then evaluating them by different data mining algorithms. We have used data classification, query analyzer, k-clustering, decision trees and association rules. Our study shows that by clustering and decision trees the applicants can be classified effectively according to the needed criteria.
Data Mining; KDD; Credit Card; K- Clustering; Knowledge discovery in database process; Classification; Query Analyzer; Decision Tree
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Lipika Barua, Atikur Rahman, Sharif Ahamed, Rasel Mia, Roena Afroz Aenney and Karam Newaz. Credit card application handling using data mining technique. World Journal of Advanced Research and Reviews, 2023, 17(2), 839-843. Article DOI: https://doi.org/10.30574/wjarr.2023.17.2.0330