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Formosa Journal of Computer and Information Science
Published by PT FORMOSA CENDEKIA GLOBAL
ISSN : -     EISSN : 28303040     DOI : https://doi.org/10.55927/fjcis.v1i2.1151
Core Subject : Science,
Computer Science & IT
Formosa Journal of Computer and Information Science (FJCIS) is an international platform for scientists, academics, practitioners and engineers involved in all aspects of computer science and information sciences to publish high quality, up todate, peer review papers. It is an international research journal sponsored by Formosa Publisher. The journal provide a platform for survey, research and review articles from experts in the field, promoting insight and understanding of the state of the art, and trends in computer and information sciences. The contents include original research and innovative theory and applications from all parts of the world. The journal publish articles twice in a year (March and August).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 51 Documents
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Analysis of PT PLN (Persero)'s New Installation Waiting List Using the K-Means Clustering Algorithm Ernawati, Ernawati; Agushinta R, Dewi
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16429

Abstract

This study examines the application of the K-means clustering algorithm to analyze new installation waiting list data obtained from the last three months of 2024. Only entries categorized under new installation requests were selected as the primary dataset. The analysis began by determining the optimal number of clusters: a high volume of new installation waiting lists (C1), a medium volume (C2), and a low volume (C3). Data mining processes were carried out using the RapidMiner tool, producing the following results: 6 UIDs/UIWs were classified into the high cluster (C1), 7 into the medium cluster (C2), and 9 into the low cluster (C3). The clustering performance was subsequently validated using the Davies–Bouldin Index, yielding a final score of 0.486, consistent with the RapidMiner output.

Page 6 of 6 | Total Record : 51

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