<![CDATA[Indonesia’s labor market continues to face structural challenges characterized by disparities in human capital quality, regional economic inequality, and variations in open unemployment rates across provinces. This study aims to analyze the effect of human capital quality on labor market conditions, proxied by the Open Unemployment Rate (OUR) in 2024. Human capital is measured using the Human Development Index (HDI) and Mean Years of Schooling (MYS), while control variables include Gross Regional Domestic Product (GRDP) per capita and poverty rate. This study employs a quantitative approach using cross-sectional secondary data from 34 provinces obtained from Statistics Indonesia (BPS). A binary logistic regression model is applied to estimate the probability of provinces falling into a high unemployment category. The results indicate that the model is appropriate, with a Nagelkerke R² of 0.598 and a classification accuracy of 79.4%. Partially, HDI has a negative and significant effect on high unemployment, with an odds ratio of 0.724, implying that a one-point increase in HDI reduces the likelihood of high unemployment by 27.6%. In contrast, MYS has a positive and significant effect, with an odds ratio of 2.574, indicating a mismatch between educational attainment and labor market absorption. Meanwhile, GRDP per capita and poverty rate are statistically insignificant. These findings suggest that improvements in human capital have not been fully accompanied by structural economic transformation capable of absorbing educated labor.Keywords : Binary Logistic Regression, Human Development Index, Labor Market, Mean Years of Schooling, Open Unemployment Rate]]>
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