Integrasi AHP dan MOORA untuk Menentukan Penerima Bantuan Perumahan Tidak Layak Huni - Beki Subaeki; Yanyan Gunawan; Khaerul Manaf; Erna Sianturi; Olif Prasetyo (Departement Information Systems Universitas Kebangsaan Republik Indonesia, 2026)
Housing is a basic need that plays an essential role in human life. According to Law No. 1 of 2011, adequate housing must meet safety, health, and comfort standards. However, many people still live in uninhabitable houses due to economic limitations. The government, through the Social Rehabilitation of Uninhabitable Houses program, provides financial assistance to help low-income communities improve their homes. Nevertheless, the selection process for beneficiaries often suffers from inaccuracies in targeting because it is still conducted manually and subjectively.To address this issue, a decision support system (DSS) is developed to assist in selecting beneficiaries more objectively. This study implements a DSS that combines the Analytical Hierarchy Process (AHP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods. The results of system testing show that all stages, from entering criteria and assigning weights to ranking alternatives, operate in accordance with the applied methods, and the system can display the final ranking of beneficiaries accurately and efficiently.A comparison between manual calculations and the system's output demonstrates that the system produces identical results for the criteria weighting and alternative ranking processes. Testing was conducted using 10 criteria and 110 alternatives, with selected alternatives presented in the calculation section as representative examples to illustrate the method's stages. The AHP Consistency Ratio of 0.0278 indicates that the pairwise comparison matrix is consistent and acceptable. Furthermore, the system identified 64 eligible aid recipients based on the final MOORA ranking results and the applied eligibility rules. These results demonstrate that integrating the AHP and MOORA methods can enhance the objectivity, accuracy, and effectiveness of the aid recipient selection process.