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Combination of Adaptive Resonance Theory 2 and RFM Model for Customer Segmentation in Retail Company

by I Ketut Gede Darma Putra, A. A. Kt. Agung Cahyawan, Dian Shavitri H.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 2
Year of Publication: 2012
Authors: I Ketut Gede Darma Putra, A. A. Kt. Agung Cahyawan, Dian Shavitri H.
10.5120/7320-0110

I Ketut Gede Darma Putra, A. A. Kt. Agung Cahyawan, Dian Shavitri H. . Combination of Adaptive Resonance Theory 2 and RFM Model for Customer Segmentation in Retail Company. International Journal of Computer Applications. 48, 2 ( June 2012), 18-23. DOI=10.5120/7320-0110

@article{ 10.5120/7320-0110,
author = { I Ketut Gede Darma Putra, A. A. Kt. Agung Cahyawan, Dian Shavitri H. },
title = { Combination of Adaptive Resonance Theory 2 and RFM Model for Customer Segmentation in Retail Company },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 2 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number2/7320-0110/ },
doi = { 10.5120/7320-0110 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:43:03.874858+05:30
%A I Ketut Gede Darma Putra
%A A. A. Kt. Agung Cahyawan
%A Dian Shavitri H.
%T Combination of Adaptive Resonance Theory 2 and RFM Model for Customer Segmentation in Retail Company
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 2
%P 18-23
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Customer segmentation is one of the important issues in Customer Relationship Management (CRM). This paper demonstrated the fusion of ART 2 algorithm and RFM (Recency, Frequency, and Monetary) model to cluster the customers in Retail Company. Each cluster is validated by searching the overall average value of silhouette index. In this paper used 17. 999 rows of data transaction then was modeled into RFM model and become 499 rows of RFM data. Experiments were done by forming 2 to 6 clusters by changing the value of vigilance parameter (?) and noise suppression (?). In this paper, all clusters formed have overall average Silhouette index value more than 0, especially for 2, 3, 4 clusters formed have overall average Silhouette index value close to 1, indicates most of the silhouette value in all clusters were formed have a positive value or above zero, its means ART 2 clustering algorithm which produces two to six clusters have been able clustering well.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Customer Segmentation Rfm Model Art 2 Algorithm Silhouette Index

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