Optimizing Decision-Making for Aid Allocation in Underdeveloped Regions Using the MOORA Method

Abstract

The allocation of assistance for the Family Hope Program is a process that requires precision to ensure that assistance is given to those most in need. This research develops a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method for optimizing the selection of beneficiaries in disadvantaged villages which includes criteria used including education, toddlers, pregnant women, disabilities, elderly, income, employment, number of dependents, and house size. Each criterion is normalized and given a weight according to its level of importance. The results show that alternative A2 has the highest optimization value with Yi of 0.254, followed by A8 (0.208) and A5 (0.204). In contrast, alternatives A3 (0.029) and A10 (0.035) have the lowest optimization value. Matrix normalization and criteria weights show the significant influence of the criteria of education, pregnant women, elderly, income, number of dependents, and house size in the selection process. The implementation of DSS with the MOORA method is proven to increase efficiency and accuracy in the selection process of Family Hope Program beneficiaries, reduce subjective errors, and ensure assistance is channeled to those who really need it. Therefore, the MOORA method is recommended as an effective tool to optimize social assistance allocation, increase transparency, and reduce bias in decision-making.