Segmentasi Pelanggan Menggunakan Fuzzy C-Means Clustering berdasarkan RFM Model pada E-Commerce (Studi Kasus: E-Commerce XYZ) - Arieftia Wicaksono; Fitra Abdurrachman Bachtiar; Nanang Yudi Setiawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
E-Commerce XYZ is a marketplace site owned by a state-owned telecommunications company. There are various kinds of purchasing behavior of e-commerce users in Indonesia. With customer segmentation, e-commerce XYZ can find out information related to existing customer behavior to attract new potential customers and retain loyal customers. The data used in this research were transaction data from January 1, 2020 to April 30, 2020 with a total of 78,262 transactions. This customer segmentation process is segmented based on Recency (the number of days needed between two purchases), Frequency (number of purchases within a certain period), and Monetary (the amount of money spent in a certain period) or commonly referred to as the RFM model. The segmentation technique used is clustering with the Fuzzy C-Means Clustering method. Elbow method is used to determine the best number of clusters. This research resulted in customer segmentation into 2 and 3 clusters. The cluster results will be validated and verified using the silhouette coefficient and euclidean distance to determine the best cluster. The validation results using the silhouette coefficient for cluster 2 and cluster 3 are 0.703 and 0.645, respectively. The results of segmentation based on the RFM model will be visualized using a dashboard to help stakeholders see the purchasing behavior of each cluster. The dashboard is evaluated using the System Usability Scale (SUS) to determine its usability level. The results of the dashboard evaluation are 97.5, these results are included in Grade "A" and Adjective Rating "Excellent". With these results, the XYZ E-Commerce dashboard that was created is functioning properly for stakeholders.