Poverty is a serious issue that is hard to ignore in many Indonesian provinces, especially the province of Central Java. This study uses secondary data in the form of a datapanel with cross-section 35 districts / cities and time series for 6 years to measure four independent variables—the city minimum wage (UMK), open unemployment, the human development index (HDI), and foreign investment—and one dependent variable—the poverty variable (Y). The goal is to determine the factors that affect poverty in the province of Central Java. This study's data analysis technique is panel data regression with a Fixed Effect Model (FEM) approach, which is handled with version 12 eviews. Because the District Minimum Wage (UMK) variable had a probability value of 0.0001 < 0.05 and a coefficient value of -5.73000, the study's findings demonstrated that it had a negative and substantial impact on poverty. With a prob value, the Open Unemployment variable statistically significantly and favorably affects poverty. 0.0000 less than 0.05. Furthermore, because the HDI variable has a prob value, research has demonstrated that it significantly and negatively affects poverty. the HDI's ability to lower the number of people living in poverty (0.0008 < 0.05). However, because the Foreign Investment variable has a low value, it was unable to demonstrate that it had an impact on poverty. The results indicated that the poverty rate was unaffected by the amount of foreign direct investment, with 0.7696 > 0.05. The study's overall findings demonstrate that 56.8% of poverty can be described by the four independent factors, with the remaining 43.2 percent being explained by variables not included in the research model.