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All Journal Jurnal Krisnadana
Ni Putu Dea Sillviari
Sistem Informasi, Universitas Bali Dwipa, Indonesia
Computer Science & IT Control & Systems Engineering

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K-Means Clustering of Students’ Anxiety Levels Based on DASS-42 Socres Ni Putu Dea Sillviari; Ayu Gde Chrisna Udayanie
Jurnal Krisnadana Vol 5 No 2 (2026): Jurnal Krisnadana- January 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/krisnadana.v5i2.1097

Abstract

Anxiety is a psychological state that may adversely influence students’ focus, thinking ability, and academic achievement. This study seeks to group students’ anxiety levels using the K-Means clustering method based on DASS-42 questionnaire scores. The dataset consisted of responses from 835 tenth-grade students enrolled at a private vocational high school in Gianyar, Bali. In the preprocessing phase, 14 anxiety-related items from the DASS-42 scale were selected, and an overall anxiety score was computed for each participant. The K-Means algorithm was applied with five clusters (K = 5) corresponding to anxiety categories: normal, mild, moderate, severe, and extremely severe. The clustering process generated centroid values of 4.20, 9.15, 13.69, 19.30, and 27.50, respectively. The results showed that most students were grouped into the moderate anxiety cluster, representing 32% of the total sample. Meanwhile, 24% were classified as normal, 11% as mild, 19% as severe, and 14% as extremely severe. When compared with the standard DASS-42 classification, the K-Means approach demonstrated greater flexibility than interval-based methods. The findings are expected to help schools better understand students’ psychological conditions through computational analysis and support informed educational decision-making.
Co-Authors Ayu Gde Chrisna Udayanie