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Ramadhani, Indah
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

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Penerapan Algoritma Fuzzy C-Means untuk Klasterisasi Customer Lifetime Value menggunakan Model LRFMD Ramadhani, Indah; Afdal, M; Mustakim, Mustakim; Zarnelly, Zarnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7613

Abstract

PT X is a retail company engaged in printing. The company has not differentiated between information about profitable and unprofitable customers for the company. Transaction data is only used as profit and loss information so they do not know the characteristics of the customers they have. In addition, the lack of extensive services in the merchandise category is one of the reasons the company's revenue has not reached the predetermined target. Currently, the company has opened additional services in the merchandise field. This research aims to identify customer segmentation as well as analyze the characteristics and provide a strategy proposal that will be submitted to PT. X. Customer loyalty and characteristics have a significant impact on a company. To identify customers who show loyalty to the company, the Fuzzy C-Means algorithm is used to perform clustering, using the Davies Bouldin Index (DBI) to evaluate the clustering results. The model used is in accordance with the principles of Length, Recency, Frequency, Monetary and Diversity (LRFMD) to categorize purchasing patterns. By analyzing LRFMD variables, it is possible to identify customers who are loyal to the company and those who are not. This research produces 6 clusters with the best cluster or supestar customer in cluster 6, the second best value customer or golden customer is cluster 2, the average value customer or typical customer is cluster 4 and 5 and the lowest cluster or dormant customer is in cluster 3.
Co-Authors Amiruddin Amiruddin Fitriani, Nurul Fitriani, Ranty Hamzah Hasyim Hastuti, Hera hasyim, hasyim Izzatika, Meiliza Luchia, Nanda Try M Afdal Megawati - Mustakim Mustakim Novrikasari Novrikasari, Novrikasari Nur Alam Fajar Rahmadeyan, Akhas Sari, Wulan Kurnia Sopianti, Maya Tasia, Ena Tuzzahra, Aquila Haya Yuanita Windusari Zahra, Raudiatul Zarnelly Zarnelly