<![CDATA[The purpose of this study is to determine the effect of GRDP, HDI, and total population on the amount of poverty in South Sumatra. The type of data used in this study is secondary data in the form of document data on GRDP, HDI, Total Population, and Total Poverty for a period of 3 years (2016-2018) in 17 (seven) districts/cities of South Sumatra Province. The data analysis technique used in this study is panel data regression with data processing tools using Eviews 11. To perform regression on the variables, the researcher uses 3 (three) methods, namely: (a) Common Effect Model, (b) Fixed Effect Model , (c) Random Effects.The results obtained simultaneously are F arithmetic > F table (244.3836 > 2.01), and the probability value is 0.000000 so that H0 is rejected and H1 is accepted. This shows that the variables GRDP, HDI, and Total Population together (simultaneously) have a significant effect on poverty. While partially the GRDP (x1) and Population (x3) variables partially have no effect on the amount of poverty, with coefficient values of 0.000270 and 0.108607 with probability values of 0.1165 (> 0.05) and 0.0000 ( <0.05). However, the HDI variable (x2) partially has a negative and significant effect on poverty, with a coefficient value of -12.82782]]>
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