Metode K-Means Clustering dengan Atribut RFM untuk Mempertahankan Pelanggan - Stephen Aprius Sutresno; Ade Iriani; Eko Sediyono (Jurnal Teknik Informatika dan Sistem Informasi, 2018)
The effort to keep customers is one of the important CRM strategies in each business that can increase profits for the company. The XYZ workshop which became the case study in this study focused more on attracting customers than implementing customer retention strategies. The aim of this research was to analyze customer transaction data in the XYZ workshop using the K-Means clustering method with RFM attributes to classify customers and determine appropriate strategies to retain customers. This research was conducted using a descriptive research method with a quantitative approach, whereas data analysis was carried out through the stages of data selection, preprocessing, transformation, processing and continued with RFM strategy analysis. The results of this study obtained 5 clusters with different strategies according to the RFM score obtained. This strategy can be used by XYZ workshop as a strategy to retain customers to provide more benefits.