Abstract
In recent years, the development of machine learning in construction as well as the preparation of appropriate software aims to provide improved solutions to potential safety hazards and risks within the construction environment. However, the fatalities and injuries in construction sites still happened frequently, and the high numbers of accidents and casualties make construction work the most hazardous occupation. This study aims to analyze the prioritize of artificial intelligence (AI) important factors in construction safety using the AHP method. Construction safety practitioners were selected as the respondent. The hierarchy was established consisting of five (5) factors, which were subsequently categorized into twelve (12) sub-factors. With 25.43 percent, jobsite was determined to be the most significant AI element in construction safety, followed by technology component with 25.37% and human error with 22.76%. The subfactors that prioritize are noticed to safety officers when workers disregard safety on the construction site with 69.21%, cloud computing technique, inspecting, controlling, and training with 60.04%, and AI in construction safety can predict the possible issues with 14.29%. The findings of this study can help software developers in determining the level of priority for the use of AI in the safety aspect of construction sites.
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