Random Forest Approach in Prediction Workers' Stress from Personality Traits
Jungsook Kim, Daesub Yoon, Hyunsuk Kim · 2022 13th International Conference on Information and Communication Technology Convergence (ICTC) · 2022
Continuous exposure to stress threatens the physical and mental health of workers and reduces their quality of life. On the business side, stress has negative consequences, such as reduced productivity. Therefore, it needs to assess and manage stress. In this study, we assess stress using workers' personality traits collected from online surveys. Stress was measured by the VAS tool and classified by stress and normal groups. As a result of the experiment, the Random Forest model with the personality traits as input features was able to classify stress with an accuracy of 81 %. It was feasible to improve the accuracy by 90% by adding dynamic factors.