Analysis of Turnover Intention Factors Using the Partial Least Square Structural Equation Modeling (SEM-PLS) Method

The decline in human resources and high turnover rates continue to be global issues that organizations need to address. PT XYZ faces a significant challenge with a fixed employee turnover rate of 10% in 2023. Given the high turnover rate, it's crucial to identify the factors influencing employees' intentions to leave in order to mitigate this trend. This study aims to develop a research model that incorporates six variables: job stress, job satisfaction, compensation, commitment, work environment, and turnover intention, which will be tested through 13 hypotheses. Data collection will be conducted through purposive sampling of employees at PT XYZ, using questionnaires distributed via Google Forms and analyzed using the SEM-PLS method. The findings indicate that job satisfaction, compensation, and a supportive work environment significantly negatively impact job stress and turnover intention, while job stress significantly positively affects turnover intention. No significant effects of commitment on job stress or turnover intention were found, suggesting that commitment alone may not be a strong independent factor in managing job stress or retention. The implications of this study suggest that the company should enhance job satisfaction, adjust compensation, and improve the work environment while reducing job stress to decrease turnover intention.