Improving social welfare through the provision of Direct Cash Assistance for village funds is one of the government's efforts to support the rural economy. In the distribution process of this assistance, precise coordination and analysis are necessary to ensure that each program is targeted accurately without any elements of misappropriation. Direct Cash Assistance for village funds has several criteria that must be met by potential recipients, necessitating a multi-criteria decision support method to determine candidates who meet these criteria at the most appropriate level. In addressing various challenges such as inaccurate targeting and lack of transparency in fund distribution, time-consuming data processes, and the neglect of differences in criteria values can slow down the decision-making for aid recipients. In this research, the use of the Entropy Method for optimizing criteria weighting in problem resolution is significant. The obtained weights are then integrated with the Multi-Attributive Border Approximation area Comparison (MABAC) method, aiming to determine the ranking of aid recipients most suitable. Finally, the ranking results are interpreted as identifying the candidates most fitting to receive direct cash assistance for village funds.