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Classification Of Loyality Customer Using K-Means Clustering, Studi Case : PT. Sucofindo (Persero) Denpasar Branch Charolina Devi Oktaviana Soleman; Nyoman Pramaita; Made Sudarma
International Journal of Engineering and Emerging Technology Vol 5 No 2 (2020): July - December
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/IJEET.2020.v05.i02.p28

Abstract

The success of the company in developing its services can be seen from the number of customers who use these services, customer loyalty in using services can be seen from customer loyalty. Customer loyalty is an important factor in the development of a business in the company, repeated use of services can be used as an indicator in determining the level of customer loyalty, by paying attention to customer loyalty, of course the company will be able to develop customer focus on an ongoing basis. Clarification of customers needs to be done to find out how demographics customers use services, can be seen from how many customers and the level of transactions made. K-Means clustering is one method that can be used for the classification process of customer data through transactions carried out by forming several clusters, this classification process is divided into 5 clusters with the results of which include 1) A few small number transactions with many customers, 2) Many transactions small number with many customers, 3) a few transactions with a medium number of customers begin to decrease, 4) a few large number transactions a few customers, 4) a moderate number of transactions with a number of customers.