Segmentasi Nasabah Kartu Kredit Berdasarkan Perilaku Penggunaan Kartu Kreditnya Menggunakan Algoritma K-Means

Ichwanul Muslim Karo Karo


The intensity of credit card customers in transacting has increased in the last 10 years in Indonesia. This is a challenge as well as an opportunity for the Bank. Customer segmentation information is very useful for reducing bad credit or increasing customer credit card limit capacity. This panel aims to segment credit card customers based on their credit card usage behavior with a clustering approach using the K-means algorithm. Meanwhile, the evaluation process of segmentation results uses a sillhoette index. Based on the experimental results, the best number of clusters is six groups. The six groups are shopping hobbies, payment processing when due, payments in installments, withdrawing cash, buying expensive goods, and types that rarely use credit cards.


K-Means; sillhoette index.

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