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All Journal Journal of Software Engineering and Information System (SEIS)
Ramadhan, Fauzan Purnama
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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IMPLEMENTASI K-MEANS MENGUKUR KEPUASAN SISWA TERHADAP PELAYANAN PADA SMKS PELITA RAYA JAMBI Saputra, Vanji; Rifaldi, Dianda; Ramadhan, Fauzan Purnama; Mulyadi, Iriene Putri
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 1 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i1.9636

Abstract

Education plays a strategic role in improving the quality of human resources; therefore, the quality of educational services must be continuously evaluated. Student satisfaction is an important indicator in assessing school service quality, as students actas the primary customers of educational services. SMK Swasta Terpadu Pelita Raya Jambi needs to measure student satisfaction to enhance service quality and institutional competitiveness.This study applies a data mining approach using the K-Means Clustering algorithm to analyze student satisfaction with school services. Data were collected through questionnaires distributed to 319 students using a Likert scale. The measurement of student satisfaction was based on five service quality dimensions: tangibles,reliability, responsiveness, assurance, and empathy. The research stages included data collection, data cleaning, data transformation, and data processing using both manual calculations and SPSS software.The results indicate that student satisfaction data were grouped into three clusters. The first cluster consisted of 183 students who were satisfied with school services, the second cluster included 30 students who were moderately satisfied, and the third cluster comprised 106 students who were dissatisfied. The clustering results obtained using SPSS showed a similar pattern, although slight differences in cluster membership occurred due to random centroid initialization.In conclusion, the K-Means algorithm effectively clusters student satisfaction levelsand provides valuable insights for school management. The clustering results can serve as a basis for evaluating and improving service quality to enhance student satisfaction at SMK Swasta Terpadu Pelita Raya Jambi
Co-Authors Dianda Rifaldi Mulyadi, Iriene Putri Saputra, Vanji