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All Journal Jurnal Teknik Industri
Fauziah
Department of Mechanical and Industrial Engineering, Makassar State University, Makassar, Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering

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Safety Sign Ergonomic Risk in Industrial Area Offices Validation using Artificial Intelligence (AI) based on Electroencephalography (EEG) Signals Zulfahmi Noor; Muhammad Noor Arridho; Fauziah
Jurnal Teknik Industri Vol. 27 No. 2 (2026): August
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol27.No2.117-132

Abstract

Ergonomic hazards are one of the occupational hazards that are not yet supported by validated and widely used safety signs, so that workers' understanding of these risks is still relatively low. This study aims to identify the needs, design, and validate ergonomic risk safety signs in the office area of ​​PT Berau Coal. The study was conducted through observation, interviews, identification of user needs, design of 14 safety signs consisting of 6 warning signs and 8 command signs, and testing the level of understanding of 8 respondents. Validation was carried out using two approaches, namely direct statements and synchronized through Electroencephalography (EEG) signal analysis classified using the Support Vector Machine algorithm. The results showed a level of understanding of 97% based on direct questions and 92.35% based on EEG analysis. The difference in results indicates that EEG-based evaluation provides a more objective assessment of workers' cognitive responses compared to subjective assessments through direct answers. These findings indicate that the developed safety signs have a high level of understanding and have the potential to be an objective approach in evaluating ergonomic safety signs in the work environment.
Co-Authors Muhammad Noor Arridho Zulfahmi Noor