Indonesian Journal on Computing (Indo-JC)
Vol. 6 No. 1 (2021): April, 2021

Implementation of K-Means++ Algorithm for Store Customers Segmentation Using Neo4J

Arief Chaerudin (Unknown)
Danang Triantoro Murdiansyah (Universitas Telkom)
Mahmud Imrona (Unknown)

Article Info

Publish Date
03 May 2021


In the era of data and information, data has become one of the most useful and desirable things. Data can be useful information if the data is processed properly. One example of the results of data processing in business is by making customer segmentation. Customer segmentation is useful for identifying and filtering customers according to certain categories. Analysis of the resulting segmentation can produce information about more effective target market, more efficient budget, more accurate marketing or promotion strategies, and much more. Since segmentation aims to separate customers into several categories or clusters, a clustering algorithm can be used. In this research, customer segmentation is carried out based on the value of income and value of expenditure. The categorization method that will be used for this research is to use the K-Means ++ algorithm which is useful for determining clusters of the given data. In this study, the implementation of K-Means ++ is carried out using Neo4J. Then in this research, a comparison of K-Means ++ and K-Means is carried out. The result obtained in this study is that K-Means ++ has a better cluster than K-Means in term of silhouette score parameter.

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Journal Info





Computer Science & IT


Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University ...