<![CDATA[This paper aims to investigate the linkage and explore what has determined the unemployment rate in Indonesia from 2000 to 2021 which include literacy rate, school enrolment, labour force participation and household and non-profit institutions serving households (NPISHs) as the main explanatory variables. To control factors of unemployment and avoid spurious or misleading results, other than FDI, we include other macroeconomics variables such inflation, trade and interest rate. This study deploys timeseries regression and Ordinary Least Square (OLS) as the regression technique to estimate the coefficients of the linear function that best fits the data. To assess the model's assumptions and diagnose any potential issues that may affect the model's reliability and validity, the author applied heteroscedasticity, normality, multicollinearity, and autocorrelation test. All data are attained from World Development Index (WDI). Overall, HNC is the only determinant significantly increase level of Indonesia unemployment. While the increase of FDI may exacerbate Indonesia’s unemployment rate, LFP plays significant role in reducing the unemployment rate in Indonesia. The contribution of this paper lies in providing a nuanced understanding of the specific determinants of unemployment, with a particular emphasis on the significant impact of NPISHs. Based on the findings, policymakers should think about making investments in NPISHs to spur growth in the economy while generating job opportunities. ]]>
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