Segmentasi Pelanggan Menggunakan Metode Fuzzy C-Means Clustering Berdasarkan LRFM Model Pada Toko Sepatu (Studi Kasus: Ride Inc Kota Malang) - Muhammad Taufik Dharmawan; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Ride Inc. is a leather shoe store established in 2012 in the city of Malang. Customer data owned has not been utilized to obtain values that are able to help Ride Inc. in creating business strategies to gain and retain customers. Customer segmentation is groups of customers who have a similarity of characteristics that able to provide information. The characteristics of customers can be seen by applying LRFM (Length, Recency, Frequency, and Monetary) model. Methods used in grouping customers are Fuzzy C-Means clustering. Elbow method used to help the process of determining the best number of clusters iteratively. The data used from the Ride Inc. are 522 customers data in the period of July 2017 until March 2018. The results shows that there are two and three clusters that formed based on elbow method that are then implemented into the Fuzzy C-Means. Customer segment analysis based on the LRFM model formed in the rank of profitable customer group based on the highest value of L, F, and also M and the lowest R. Dashboard visualization become the output of the research based on the value of the given LRFM to Ride Inc. The average score of usability testing from 2 respondents is 65. This means that Ride Inc. receive the dashboard visualization.