PENERAPAN FUZZY C-MEANS KLUSTER UNTUK SEGMENTASI PELANGGAN E-COMMERCE DENGAN METODE RECENCY FREQUENCY MONETARY (RFM) - Stevanus Sandy Prasetyo; Mustafid Mustafid; Arief Rachman Hakim (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2020)
E-commerce has become a medium for online shopping which is growing and popular among the public. Due to the ease of access for all internet users and the completeness of the products offered, e-commerce has become a new alternative in meeting people's needs. Currently, the competition in the business world is very fierce, any e-commerce company needs to be able to carry out the right marketing strategy to compete in acquiring, retaining, and partnering with customers. In this research, the segmentation of e-commerce customers was carried out using the Fuzzy C-Means cluster and the RFM method. The clustering process is carried out six times with the number of clusters starts from two to seven clusters. The results showed that the optimum number of clusters formed according to the Xie-Beni validity index was four clusters. The cluster becomes customer segments that have the characteristics of each customer based on their recency, frequency, and monetary value. The best segment is segment 4 which has very loyal customers in shopping on tumbas.in e-commerce. From the segments that have been formed, they can be used as a consideration in implementing the right marketing strategy for each customer. Keywords : E-commerce, customer segmentation, Fuzzy C-Means Cluster, RFM, Xie-Beni Index