Indra Jhon Fischer
Program Studi Teknik Sipil, Jurusan Teknik Sipil, Politeknik Negeri Medan

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The Development of a Fuzzy Logic-Based Sustainable Ergonomics Assessment Method for Identification of Occupational Health Risks in Construction Lisherly Reginancy Debataraja; Oktavia Ully Artha Silalahi; Fenny Novita M Sianturi; Indra Jhon Fischer; Multilawati Nasution
Journal of Civil Engineering and Planning (JCEP) Vol. 7 No. 1 (2026): JCEP
Publisher : Program Studi Sarjana Teknik Sipil Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/jcep.v7i1.11494

Abstract

Referring to ESDM Regulation Number 26 of 2018, every company is obliged to prepare an Occupational Health and Safety (K3) Program Plan as an effort to control and mitigate potential accidents and illnesses due to work activities. The construction sector itself is classified as an industry with a very high level of K3 risk compared to other sectors. Therefore, a model for applying a sustainable ergonomic risk assessment method is needed as a decision-making tool in the sustainable management of Occupational Health and Safety (K3) in construction projects. Based on research, all work activities at the reinforcement, casting, and installation/dismantling stages of formwork have a high level of ergonomic risk, especially to the back, shoulders, neck, and wrists. The application built to assess ergonomic risks using fuzzy logic is called Ergosuite. ErgoSuite is designed as a suite of tools for professionals in the fields of ergonomics, occupational health, and safety (K3). The main purpose of this application is to provide an interactive platform for conducting, storing, and analyzing ergonomic assessments, including the NIOSH Lifting Equation, REBA, RULA, and CMDQ. The fuzzy logic-based ergonomic risk assessment system demonstrates good performance in terms of technical aspects, functionality, and field application. Technically, the system is capable of performing fuzzification, defuzzification, rule base, and data integration processes with stable output and in accordance with CMDQ, REBA, RULA, and NIOSH standards. REBA, RULA, and NIOSH observations are then processed into the system through fuzzification, inference, and defuzzification.