Pengelompokan Fuzzy Pengelompokan Pelanggan Pusat Perbelanjaan Menggunakan Algoritma Fuzzy C-Means

Abstract

Customer segmentation is a crucial strategy for understanding consumer behavior and improving marketing efforts. This research aims to classify mall customers based on demographic data and shopping behavior using the Fuzzy C-Means (FCM) algorithm. The dataset employed is the "Mall Customer Segmentation Data," containing information such as age, gender, annual income, and spending score. The FCM algorithm groups customers into clusters based on data similarity, considering the fuzzy membership value for each customer. The results are expected to provide deeper insights into the characteristics of each customer group, assisting mall management in developing more targeted marketing strategies. The study will also discuss the interpretation of each cluster and the evaluation of the FCM algorithm's performance in the context of customer segmentation.