Implementation of Vocational School Management Model to Improve School Performance

Abstract

This study aims to test the implementation of the Vocational High School (SMK) management model and identify the relationship between academic-industry management, business and industry partnerships (DUDI), sustainable quality management, and human resource management with school performance. The study uses a quantitative approach with an explanatory survey design on 50 observations at SMK in Tomohon City and analyzes six latent constructs measured through 52 indicators using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results show that academic-industry management has a positive effect on the SMK Management Model (β = 0.215; p = 0.046), while DUDI partnership management has a positive effect on the SMK Management Model (β = 0.687; p = 0.001) and SMK Performance (β = 0.426; p < 0.001). Human resource management also has a positive effect on the SMK Management Model (β = 0.307; p = 0.012) and SMK Performance (β = 0.067; p = 0.011), while sustainable quality management shows a strong direct relationship with SMK Performance (β = 0.621; p < 0.001), but does not show a significant relationship with the SMK Management Model (p = 0.165). The SMK Management Model has a negative and significant relationship with SMK Performance (β = −0.102; p < 0.001), a finding that needs to be interpreted with caution due to indications of collinearity and closeness between the constructs. The model explains 71.4% of the variance in the SMK Management Model and 99.2% of the variance in SMK Performance, but the high apparent power needs to be read in conjunction with the HTMT and VIF findings which indicate issues of discriminant validity and collinearity. This study contributes to the development of vocational education management studies by showing that SMK performance needs to be understood as a result of the relationship between academic orientation towards the world of work, DUDI partnerships, sustainable quality management, and human resource development, while emphasizing the need for refinement of model specifications and robustness testing on larger samples before the model can be generalized more widely.