<![CDATA[A The purpose of this study is to determine the impact of corruption on poverty in Indonesia. The type of data taken is secondary data, time series 2007 - 2022. Corruption data, namely CPI, is sourced from Transparency International, while poverty data, HDI and TPT are sourced from BPS. The analysis technique used is multiple linear regression analysis using the classical OLS method. The results showed that corruption has a negative effect on poverty. This result is in accordance with the proposed hypothesis that increasing corruption (CPI declines) causes poverty to increase. The second variable, HDI, also has a negative effect on poverty, while TPT has a positive effect on poverty in Indonesia. The three variables have the ability to explain poverty by 94.4%.]]>
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