<![CDATA[Poverty is still a major problem in the development of a country, one of which is Indonesia. The government implements various programs to eradicate poverty, one of which is through social protection. This research aims to determine the characteristics of poverty with the social insurance index and the influence of education, TPT, GRDP, HDI, population density, and social insurance on poverty in Indonesia in 2023. The social insurance index has been previously formed using factor analysis with the principal component analysis method . The characteristics of poverty with the social insuranceindex are described using distribution maps and quadrant analysis. There are similarities in the poverty distribution pattern with the social insuranceindex. Meanwhile, in the quadrant analysis, an inverse relationship was found between the poverty level and the social insurance index. Then, to find out the effect of education, TPT, GRDP, HDI, population density and social insurance on poverty in Indonesia in 2023, it was analyzed using multiple linear regression analysis with the ordinary least squares method. The research results show that there is a significant influence simultaneously for all independent variables, but partially only education, GRDP, HDI and social insurance significantly influence poverty in Indonesia in 2023. Only the education variable has a positive influence on poverty, while GRDP, HDI, and social insurance have an influence negative on poverty.]]>
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