JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Vol. 9 No. 5 (2025): October 2025

Enhancing Clustering Accuracy Using K-Means with Seeds Optimization

Mahiruna, Adiyah (Unknown)
Ngatimin, Ngatimin (Unknown)
Destriana, Rachmat (Unknown)
Rachmawanto, Eko Hari (Unknown)
Yuliansyah, Herman (Unknown)
Hidayat, Muhammad Taufiq (Unknown)



Article Info

Publish Date
08 Oct 2025

Abstract

In this study, the development of the Mean-based method proposed by Goyal and Kumar will be carried out by changing the initial cluster center determination step, which was originally based on the origin point O (0,0), to be replaced with the arithmetic mean. To assess the performance of the proposed method, it will be compared with the Global K-means method and the Mean-based K-means method. In this study, the performance of these methods will be measured using the Davies-Bouldin Index, and the significance of the proposed method will be measured using the Friedman Test. This study proposes a method of Improving K-Means Performance through Initial Center Optimization based on Second Global Average for Clustering Osteoporosis Diagnosis of lifestyle factors. Evaluation of K-Means performance through Initial Center Optimization based on Second Global Average with DBI measurements. The targeted experimental results of this study include improving the performance of K-means optimized through the initial center based on Second Global Average. From the results of nine experiments with the number of clusters [2,3,4,5,6], it can be seen that the method proposed in this study has the same superior performance compared to the Mean Based method and compared to the Global K-means method.

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Journal Info

Abbrev

JAIC

Publisher

Subject

Computer Science & IT

Description

Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan ...