This study aims to determine the independent variables or sectors of agriculture, mining, industry, trade, and economic growth that significantly influence the open and underemployed unemployed rates. This study uses multiple linear regression analysis tools with cross-sectional data using both logs and no logs in determining the influence of agriculture, mining, industry, trade, and economic growth variables using secondary data in 2017.The regression results on TPT without logs show that only the Mining and Growth variables are insignificant. In contrast, the Agriculture, Industry, and Trade variables are significant, others are significant at 1% alpha, and the mining variable is significant at alpha 10%. And the semi-unemployed regression results without logs, only the Mining and Growth variables are insignificant. In contrast, the others are significant at 1% negligence, and the regression results using logs show that only the Mining and Growth variables are insignificant. In comparison, the Trade variable is significant at 10% alpha.Every increase in the distribution of the Agricultural Sector in GRDP by 1% will cause a decrease in TPT by 0.043% and an increase in SM by 0.218%. Every increase in the distribution of the Industrial Sector GRDP by 1% will cause an increase in TPT by 0.039% and a decrease in SM by 0.681%. Every increase in the distribution of the Trading Sector in GRDP by 1% will cause an increase in TPT by 0.078% and a decrease in SM by 0.071%. Economic growth and the mining sector have very little value, so it cannot explain the impact of this sector on TPT and SM.
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