PENGELOMPOKAN TRANSAKSI KARTU DEBIT PERBANKAN MENGGUNAKAN ALGORITMA K-MEANS - Iwan Irawan; Reza Rahman; Arief Wibowo (Jurnal Sistem Informasi dan Informatika (Simika), 2025)
One of bank customers' most widely used non-cash payment methods is making payments to merchants using debit cards. The data generated from these transactions can be utilized effectively by banks. This study analyzes customer spending habits through debit card transactions, employing a data mining technique called K-means clustering. By identifying patterns in customer transactions, the research aims to assist business units in developing targeted product strategies. The analysis determined that four clusters were optimal, resulting in a tightly grouped dataset with an average distance of 5.764 from the respective cluster centers. Grouping nominal transactions based on the date and time of the transaction can provide valuable insights for bank management when considering customer fund allocation.