Customer Segmentation Using Fuzzy C-Means Method and Fuzzy Rfm - Mayadewi, Paramita; Ananda, Dahliar; Nur Paramadina, Tria (International Journal of Engineering and Technology, 2019)
The study was conducted to explore the application of data mining in customer segmentation for laundry business. Intense competition in similar business encourage the company to manage its customer optimally. With a large number customers, the problem that has to be faced is how to determine potential customers. The process conducted is to divide customers into several segments with the aims to build customer profiles based on patterns of transactions that have been carried out.  Customer profile that is created is a profile that shows the potential level of the customer. There are five categories of potential customers form highest to lowest. Implementations is done using two methods of data mining, namely clustering, and segmentation. Clustering method using Fuzzy C-Means algorithm while segmentation using Fuzzy RFM (Recency, Frequency, and Monetary) models. Studies conducted succeeded in  grouping customers based on transcations conducted (Recency, Frequency, and Monetary). Therefore the mining results can be used to assist companies in the process of identifying the customer and also as an alternative marketing strategy.