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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Putri Lo, Angel Aprilia
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Computer Science & IT

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Behavioural Predictors of Forward Head Posture Risk: A Correlation, Machine Learning, and Clustering Analysis Putri Lo, Angel Aprilia; Christian, Christian
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.12089

Abstract

Forward Head Posture (FHP) has become increasingly common among university students due to prolonged digital device use and inadequate ergonomic behaviour. This study aims to identify the behavioural factors that most strongly predict neck tension, which is used as an indicator of FHP risk, among laptop users at Universitas Ciputra. A total of 141 survey responses were collected, capturing digital lifestyle patterns that include screen exposure, posture habits, ergonomic awareness, physical activity, and screen-related symptoms. The analysis followed a complete methodological sequence that involved data preprocessing, correlation testing, supervised machine-learning modelling, and K-Means clustering. The results show that headache after screen use, frequency of head-down posture, ergonomic knowledge, and weekly exercise emerged as the most influential behavioural predictors of neck tension, with head-down posture demonstrating the strongest association (r = 0.437). Correlation testing supported three of the four hypotheses, while the Random Forest model achieved the highest predictive performance (71.01% cross-validated accuracy). The clustering analysis revealed two distinct behavioural subgroups with different ergonomic risk profiles. These findings highlight specific behavioural targets that can support ergonomic-awareness efforts and help reduce the likelihood of FHP development in academic environments.
Co-Authors christian christian