This study aims to measure four independent variables and one dependent variable using secondary data in the form of panel data comprising 27 districts/cities in a cross-section and a time series over 5 years. The data analysis method employed is panel data regression with the random effects method. Eviews version 12 was utilized for data processing, including testing classical assumptions, hypothesis testing, and testing the Adjusted coefficient of determination (R2). The research findings indicate significant relationships between specific variables and educated unemployment. Economic Growth negatively and significantly impacts educated unemployment, demonstrating its ability to decrease educated unemployment in the region. Minimum District Wage positively and significantly influences educated unemployment, implying that increasing UMK in an area can elevate the number of educated unemployed individuals. Additionally, the Human Development Index (HDI) exerts a negative and significant effect on educated unemployment, suggesting that higher HDI can reduce educated unemployment. However, foreign investment does not significantly affect educated unemployment. Overall, the study shows that these four independent variables explain 67.8% of educated unemployment, while the remaining 32.2% is influenced by factors beyond the study's scope.
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