PENGELOMPOKAN DATA TUNGGAKAN PEMBAYARAN KREDIT MOBIL MENGGUNAKAN METODE CLUSTERING (STUDI KASUS: CV CITRA KENCANA MOBIL)
Abstract
Arrears or installments are one of the problems for companies in dealing with customers who have delays in paying pre-approved car installment bills, while the cause of arrears in car payment installments is because of the necessities of life and problems that will occur in the future no one can predict. If at the beginning the payment was smooth, it is not certain that in the future there will be no customers who are late paying installments until they have to be withdrawn. (I Wayan Sudirman, 2000). CV Citra Kencana Mobil Medan is a company that sells used and new cars with credit and cash payment systems. Due to the many problems that occur in arrears of car installment payments made by customers in 2017-2022 which causes data to accumulate, and it is also difficult for companies to provide information and follow-up in dealing with problems to customers quickly, therefore it is necessary to have a method in processing these data by clustering customer data. Based on the research conducted, there were 3 groups of 20 data, namely group 1 with 7 data and 2 groups with 8 data and group 3 with 5 data, with the most results in cluster 2, namely the data group for arrears in car loan payments in the car brand group ( X) is the Honda Jazz RS, and for the sub-district group (Y) which is in arrears, namely Medan Amplas which is in arrears (Z) for 1-4 months.
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