<![CDATA[The risk of work accidents that can be experienced by project workers is very high in the world of construction. This can be caused by behavioral factors, one of which is project workers' indiscipline in wearing Personal Protective Equipment (PPE), which can endanger the personal safety of project workers. By utilizing Artificial Intelligence technology, with the computer vision domain, researchers created a PPE detection application using the YoloV5 algorithm. The stage of creating this detection application starts from the process of problem scoping, data acquisition, data exploration, modeling, evaluation and deployment. The dataset used in making this application was taken from Saravana Alagar via Google Drive, covering 4 PPE objects, namely helmets, masks, vests and shoes. By conducting a training dataset of 100 epochs, the percentage results given were very good, namely helmets 96%, vests 96%, masks 95%, and shoes 92%. It is hoped that making this application can minimize cases of work accidents that occur in the project worker area and can increase discipline in using project PPE]]>
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