Segmentation Analysis of Students in X Course with RFM Model and Clustering - Yanuar Rafi Rahadian; Bambang Syairudin (Jurnal Sosial Humaniora, 2020)
In the business world, the competition to maintain and obtain more customershas become tougher. The presence of new players entering the market isdriven by the developments of internet and advertisement. The X guitar courseis an institution engaged in the field of non-formal education services. Thecustomers are the course student that has made the payment transaction. Themap of customer segmentation is one of the most important components infinding the main needs of each customer. Know the main needs of eachcustomer is expected to increase the customer’s loyalty. Customersegmentation can be done by using the clustering method through a datamining approach in the form of RFM (Recency, Frequency and Monetary)Models. Recency is the data of the last payment transaction date. Frequencyshows the number of course payment transactions. Monetary comes from thenominal amount of the transaction. RFM data is combined with the FuzzyGustafson-Kessel and K-Means clustering method to produce output in theform of k-clusters of customer. The formed segment is expected to representthe need of customers that vary by using validation process with the GlobalSilhouette Index. The customer population of the course is 225 students. It hasbeen concluded that the RFM score for each subject by using 3 FGK clustersis the optimum cluster model with the largest Silhouette Index, which is 0.523.This research is expected to provide an in-depth analysis of customersegmentation for X guitar course