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All Journal Techno Nusa Mandiri : Journal of Computing and Information Technology
Dodik Aris Setiawan
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Computer Science & IT

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MODEL FOR DETERMINING CANDIDATES FOR VILLAGE SOCIAL ASSISTANCE USING THE AHP–MOORA METHOD Hardian Oktavianto; Dodik Aris Setiawan; Guruh Wijaya; Zainul Arifin; Henny Wahyu Sulistyo
Jurnal Techno Nusa Mandiri Vol. 23 No. 1 (2026): Techno Nusa Mandiri : Journal of Computing and Information Technology Period o
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/rp2qkd88

Abstract

Social assistance programs at the village level are one of the government's efforts to reduce poverty and improve community welfare. However, in practice, the process of determining eligible beneficiaries is often carried out manually, which may lead to subjectivity, inaccurate targeting, and a lack of transparency in decision-making. This study aims to develop a decision support system that assists village administrators in determining priority candidates for social assistance in a more objective and systematic manner. The proposed approach integrates the Analytical Hierarchy Process (AHP) and the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods. The AHP method is used to determine the weight of each criterion through pairwise comparison matrices and consistency testing. Subsequently, the MOORA method is applied to normalize the decision matrix, calculate preference values, and rank the alternatives. The results show that AHP-MOORA can generate a priority ranking of potential social assistance beneficiaries. The calculated weights for the criteria respectively are Kepemilikan Tanah: 0.5579 (highest importance), Kondisi Rumah: 0.2633, Pekerjaan: 0.1219, Penghasilan: 0.0569 (lowest importance) and the value of CR is 0.0654, which is less than 0.1, indicating that the criteria weights are consistent. The ranking based on AHP-MOORA show significant differences than the earlier dataset. Based on sensitivity analysis, the high correlation values in all sensitivity tests show that the ranking results remain consistent. Furthermore, the system improves transparency and consistency in the decision-making process.
Co-Authors Oktavianto, Hardian Sulistyo, Henny Wahyu Wijaya, Guruh ZAINUL ARIFIN