This study aims to determine the determinants of the welfare of agricultural sector workers who come from poor households in rural areas. The exchange rate of farmers and the wages of farm laborers will affect the level of employment in the agricultural sector, which in turn will affect the level of rural poverty. The methodology used in this study uses a panel data regression model with a recursive equation model. The best model for unemployment estimation is the random effect model, while the best model for poverty estimation is the fixed effect model. The results showed that the daily wage of farm laborers had a significant negative effect on unemployment. This may be due to the fact that higher wages will increase the number of workers who are willing to work in the agricultural sector, so unemployment will fall. While the unemployment variable has a significant positive effect on the level of rural poverty. The practical implication of these research findings is that to reduce poverty in rural areas, efforts from the government are needed to increase the wages of farm laborers, as the government sets minimum wages in the formal sector. The higher daily wages of agricultural laborers will attract unemployed people in villages to work in the agricultural sector.