Analisis Metode Fuzzy C-Means dengan Model LRFM terhadap Segmentasi Pelanggan pada Toko Butik (Studi Kasus: Diva Collection Kota Cilegon) - Adityo Dwirahmawan; Nanang Yudi Setiawan; Djoko Pramono (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2021)
Diva Collection boutique shop is a boutique store that sells various types of women's clothing that was established in 2019 in Cilegon City. The store still has not implemented a Customer Relationship Management strategy by providing different services to each customer, so that the boutique treats each customer the same. Therefore, customer segmentation is needed to find out how the nature or characteristics of customers with certain similarities are. This is useful for finding information about profitable customers. Observed customer behavior is from the LRFM process. Length (difference between the last transaction and the beginning), Recency (difference between purchase dan research), Frequency (the amount of purchase), and Monetary (total consumer spending). The clustering method used is C-Means to segment customers. The results of the K-Means and Silhoutte graphs are used to determine the optimal number of clusters before clustering. The data used is data for the period August 2019 to December 2019 as many as 560 customer transaction data. the number of groups produced is 2 segments and 3 segments. Group 2 is the most optimal group, this is based on a ranking based on the highest F, M, L values and the lowest R. The Dashboard visualization of the grouping results is described in the form of diagrams and graphs. There are 3 pages that display information on the results of grouping and are given to the Diva Collection Boutique Store for testing. The average result obtained from 3 respondents is 72.5. This value is classified as good, where the Diva Collection Boutique can receive the results of the Dashboard visualization..