Customer Segmentation with RFM Model using Fuzzy C-Means and Genetic Programming

One of the strategies a company uses to retain its customers is Customer Relationship Management (CRM). CRM manages interactions and supports business build mutually beneficial relationships between companies customers. The utilization information technology, such as data mining used manage data, critical in order be able find out patterns made by when processing transactions. Clustering techniques are possible generated from customer transaction data. Fuzzy C-Means (FCM) one best-known most widely fuzzy grouping methods. iteration process carried determine which right cluster based on objective function. local minimum condition where resulting value not lowest solution set. This research aims solve problem FCM algorithm using Genetic Programming (GP), evolution-based algorithms produce better clusters. result compare application c-means genetic programming (GP-FCM) for segmentation applied Cahaya Estetika clinic dataset. test results GP-FCM yielded an function 20.3091, while algorithm, it was 32.44741. Furthermore, evaluating validity Partition Coefficient (PC), Classification Entropy (CE), Silhouette Index proves that quality gp-fcm more optimal than fcm. this study indicate produces algorithm.