Daniel Pradipta Hidayatullah
Fakultas Ilmu Komputer, Universitas Brawijaya

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Analisis Pemetaan Pelanggan Potensial Menggunakan Algoritma K-Means dan LRFM Model Untuk Mendukung Strategi Pengelolaan Pelanggan (Studi Pada Maninjau Center Kota Malang) Daniel Pradipta Hidayatullah; Retno Indah Rokhmawati; Andi Reza Perdanakusuma
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Customer Relationship Management is all that is related between the company with the customer, whether it's sales or any other service. Maninjau Center is a company that sells fashion products in Malang. The purpose of this study was to determine the value of customers who are similarly characterized then grouped and given a customer management strategy at Maninjau Center 2016. Research in this paper begins through the stages of business understanding, interviews and direct observation. The next step collects customer transaction data, then prepocessing data by selecting the required data only. Then look for customer value with corresponding LRFM parameter (Length, Recency, Frequency and Monetary). Then apply the K-Means algorithm to generate customer clustering. The value of K on the K-Means algorithm is determined at the beginning of 4. After the clustering operation is done, the cluster will be plotted with customer value matrix and customer loyalty matrix to know the characteristics of each customer segment. Last, customer will be given a marketing strategy proposal. The results obtained from the Maninjau Center case study show that the customer segment formed is four clusters, cluster 1 is 2, cluster 2 is 41, cluster 3 is 3 and cluster 4 is 657. The result of marketing strategy is in accordance with customer characteristic in every- each clustering is formed.