Abstract—Sales fluctuations are risks that must be faced by business people, PT. Gunung Hijau Success experienced this in 2016, with GAP being quite high. By giving rewards to loyal customers, it is expected to stabilize sales in the next period. So the company needs customer grouping based on customer loyalty to reward. The application of data mining can be used as an analysis to determine the loyal customer inventory according to the total purchase. In the data mining method, the clustering algorithm is one of the most popular to use where the data belonging to the same cluster will be close to each other and will be far from the data about another cluster. The results obtained in the form of customer information with criteria not loyal, loyal, and very loyal based on sales data in 2016. Also, customer criteria information from the clustering process can be used as a reference to determine the reward for customers.
Index Terms—Clusttering, k-means algoritm, customer loyalty, marketing.
Joanna Ardhyanti Mita Nugraha is with the Department of Informatics Engineering, Universitas Atma Jaya Yogyakarta, Babarsari Street No. 43, Yogyakarta, Indonesia (e-mail: joanna.mita@uajy.ac.id).
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Cite:Joanna Ardhyanti Mita Nugraha, "Application of K-Means Algorithm for Costumer Grouping," International Journal of Computer Theory and Engineering vol. 12, no. 2, pp. 59-62, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
