Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering - Syahroni Hidayat; Ria Rismayati; Muhammad Tajuddin; Ni Luh Putu Merawati (Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro, 2020)
One of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset using the integration of recency, frequency, and monetary (RFM) analysis and fuzzy c-means (FCM) algorithm to evaluate the loyalty of the entire school that has bound the partnership with the institution. The dataset is converted using the RFM approach before processed with the FCM algorithm. The result reveals that the schools can be segmented, respectively, as high potential (SP), potential (P), low potential (CP), and very low potential (KP) categories with PCI value 0.86. From the analysis of SP, P, and CP, only 71 % of 52 school partners categorized as loyal partners.