PENGELOMPOKKAN LOYALITAS PELANGGAN DENGAN MENGGUNAKAN KOMBINASI RFM DAN ALGORITMA K-MEANS

With so many companies engaged in the same field, the level of competition is very high, so that it will provide a threat for companies to lose customers. To overcome this problem companies can use information technology to process the grouping of customer data that has high loyalty to the company. This can be done quickly with high accuracy even though the amount of customer transaction data is very large and the level of complexity is high. One way that can be used to detect customer loyalty, among them is to use a Monetary Frequency Recency (RFM) analysis, and techniques for grouping can use clustering with the K-Means algorithm.