Abstract
<p><span style="font-size: 10pt; line-height: 107%; font-family: Constantia, serif;" lang="EN-US">Poverty is seen as a condition where basic rights are not fulfilled as a mandatory condition for carrying out a dignified life for the community. This research was conducted with the aim of analyzing and obtaining empirical evidence of how the provincial minimum wage <em>(Upah Minimum Provinsi-UMP)</em>, Real Per Capita GRDP, and the open unemployment rate <em>(Tingkat Pengangguran Terbuka</em>-<em>TPT</em>) can affect the number of poverty-stricken people in Indonesia in 2020. The method used in this research is quantitative, namely </span><span style="font-size: 10pt; line-height: 107%; font-family: Constantia, serif;" lang="EN-US">the </span><em><span style="font-size: 10pt; line-height: 107%; font-family: Constantia, serif;" lang="EN-US">Ordinary Least Square </span></em><span style="font-size: 10pt; line-height: 107%; font-family: Constantia, serif;" lang="EN-US">(OLS) technique, with secondary data obtained from the official website source of the Indonesian Central Bureau of Statistics (BPS), which is processed using EViews 12 software<em>.</em> <em> </em>The final results of the research showed that partially the UMP and Real Per Capita GRDP variables have a significant effect on the number of poverty-stricken people in Indonesia in 2020, while TPT has no significant effect<em>.</em> However, when all three variables were tested simultaneously, the results showed that there was a significant effect on the number of poverty-stricken people in Indonesia in 20</span><span style="font-size: 10.0pt; line-height: 107%; font-family: 'Constantia',serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-weight: bold;" lang="EN-US">20</span><span style="font-size: 10pt; line-height: 107%; font-family: Constantia, serif;" lang="EN-US">. Another result that was also shown in this study is the coefficient of determination (R2) at 0.7694 which means that 77% of the information needed to predict the dependent variable can be explained by all of the independent variables in this study.</span></p>
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