CLUSTERING CUSTOMER FOR DETERMINE MARKET STRATEGY USING K-MEANS AND TOPSIS: CASE STUDY

  • Made Agung Raharja Universitas Udayana
  • I Kadek Ari Surya Universitas Udayana
Keywords: clustering, customer, K-Means, TOPSIS, silhouette coefficient, craft, RFM, LRFM

Abstract

determining marketing strategies by companies in the midst of intense market competition. The research stage starts from preprocessing the data and then calculating the Customer Lifetime Value (CLV) through weighting the RFM (Recency, Frequency, Monetary) and LRFM (Length, Recency, Frequency, Monetary) models. The weights are given by experts with the Analytic Hierarchy Process (AHP) calculation. Then K-Means is used for the clustering process and then evaluated with the Silhouette Coefficient (SC). The best clustering results are ranked using the Technique for Orders Preference by Similarity to Ideal Solution (TOPSIS) method to produce alternative decisions in cluster selection. This research takes a case study in one of the handicraft shops in Bali which experienced a decline in product demand due to the impact of intense market competition. The results show that the SC value tends to increase along with the addition of variations in the percentage of data. The weighting of the data model from the case study expert weight resulted in the best SC value at k = 2 with the value of the RFM model of 0.665 (medium structure) and the LRFM value of 0.641. The cluster ranking validation test and Rank Consistency on the best clustering results get valid calculation results and there is no rank reversal. The recommendation for customer clusters is that Cluster 2 in the first place has 158 customers with cluster type R↓F↑M↑ with Enforced Strategy and Cluster 1 in the second place has 817 customers with cluster type R↑F↓M↓ with Let-go Strategy.

 

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Published
2022-08-25
How to Cite
Raharja, M. A., & Surya, I. K. A. (2022). CLUSTERING CUSTOMER FOR DETERMINE MARKET STRATEGY USING K-MEANS AND TOPSIS: CASE STUDY. Proceeding International Conference on Information Technology, Multimedia, Architecture, Design, and E-Business, 2, 61-71. Retrieved from https://eprosiding.idbbali.ac.id/index.php/imade/article/view/704
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