BROWSE
Detail
Conference Paper
Random Forest Approach in Prediction Workers' Stress from Personality Traits
Cited 4 time in 
Share 
Share
- Authors
- Jungsook Kim, Daesub Yoon, Hyun-suk Kim
- Issue Date
- 2022-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.1-3
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- 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.
- KSP Keywords
- Dynamic factor, Input features, Quality of life, mental health, online survey, personality traits, random forest model