Segmentasi Pelanggan Menggunakan Metode K-Means Clustering Berdasarkan Model RFM Pada Klinik Kecantikan (Studi Kasus : Belle Crown Malang) - Aulia Dewi Savitri; Fitra Abdurrachman Bachtiar; Nanang Yudi Setyawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
Belle Crown is one of new aesthetic centers in Malang has not applied CRM strategy (Customer Relationship Management) by giving different service for all of its costumers. Segmentation is a process undergo to identify costumers with similar characteristics, therefore, it can help to explore more information on profitable costumers. The costumer's business behaviour could be seen from Recency (last transaction range), Frequency (the number of transactions), and Monetary (the amount of money spent) or it is known as RFM (Recency, Frequency, Monetary). One of data clustering method is K-Means that is used to do the segmentation. The graphics result from Elbow method is used to determine the number of segments intuitively during the application of K-Means method. The data used in this research is transaction history taken from May-October 2017 and it includes 21.513 transactions and 4716 costumers. In its application, the research results two kinds of segments including 2 segments and 3 segments. The analysis based on RFM value showed that the first rate is the profitable customer as it has bigger RFM compared to other segments. The superficial of this research is to produce dashboard visualization as the result of costumers segmentation with some graphics based on RFM value of Belle Crown's service.