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- W4386850624 abstract "The intensity of credit card customers in making transactions has increased in the last 10 years in Indonesia. This is both a challenge and an opportunity for the Bank. Customer segmentation information is beneficial to reduce bad debts or increasing customer credit card limit capacity. This study aims to segment credit card customers based on their usage behavior with a clustering approach using the K-means algorithm. While the process of evaluating segmentation results using the silhouette index. Based on the experimental results, six groups are the best number of clusters. The six groups are shopping hobbies, payment process at maturity, payment by installments, withdrawing cash, buying expensive goods, and types that rarely use credit cards." @default.
- W4386850624 created "2023-09-20" @default.
- W4386850624 creator A5053912719 @default.
- W4386850624 date "2022-02-24" @default.
- W4386850624 modified "2023-10-06" @default.
- W4386850624 title "Segmentation of Credit Card Customers Based on Their Credit Card Usage Behavior using The K-Means Algorithm" @default.
- W4386850624 doi "https://doi.org/10.17509/seict.v2i2.40220" @default.
- W4386850624 hasPublicationYear "2022" @default.
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