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All Journal International Journal of Ethno-Sciences and Education Research Jurnal Dimamu Jurnal AbdiMU INTERNAL (Information System Journal)
Aryanti, Utami
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Transportation Other

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Journal : Jurnal Dimamu

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Sistem Pendukung Keputusan Pemilihan Penerima Bantuan Sosial Menggunakan Metode Simple Additive Weighting Rifasya, Pramadika; Aryanti, Utami; Anwar, Moh. Taufan; Atmoko, Dwi
Jurnal Dimamu Vol. 4 No. 1 (2024)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/dimamu.v4i1.1329

Abstract

Social assistance (bansos) is one form of government program that has become the main instrument in supporting the welfare of low-income communities in Cilaengka Wetan Village to meet their basic needs. However, the main challenge in implementing this program is the selection process for aid recipients which is often done manually, so that it risks causing inaccuracy and injustice in determining recipients. This study aims to develop a Decision Support System (DSS) for the selection of social assistance recipients in Cicalengka Wetan Village using the Simple Additive Weighting (SAW) method so that social assistance recipients are right on target and ensure that assistance is given to people who really need it. The Simple Additive Weighting (SAW) method was chosen because it is able to perform criteria-based calculations with objective and transparent results. The trial results show that the developed system can provide valid recommendations and is in accordance with the conditions of prospective recipients. This research assistance is expected to be a practical solution in social distribution, not only in Cicalengka Wetan Village but also in other areas with adjustment criteria. As a further development, an integration system with web-based technology or mobile applications can be carried out to improve the accessibility and efficiency of the decision-making process.
Implementasi Metode Profile Matching pada Sistem Pendukung Keputusan Seleksi Penerima Bantuan Rutilahu Lusiana, Novita; Aryanti, Utami
Jurnal Dimamu Vol. 5 No. 1 (2025)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/dimamu.v5i1.1757

Abstract

The Housing Improvement Assistance Program for Uninhabitable Houses (RUTILAHU) is one of the government’s efforts to improve the quality of life of low-income communities by enhancing their housing conditions. The selection process for aid recipients in Cijagra Paseh Village has traditionally been conducted manually through field surveys and village deliberations, which may lead to subjectivity, mistargeting, and a lack of transparency in the assessment process. This study aims to develop a decision support system that assists in selecting RUTILAHU aid recipients objectively and systematically using the Profile Matching method. Additionally, the system development process adopts the Waterfall methodology, which includes structured stages of requirements analysis, system design, implementation, testing, and maintenance to ensure system reliability and quality. The Profile Matching method operates by comparing the ideal recipient profile with the actual conditions of candidates through gap calculations, weighting of core and secondary factors, and generating final scores used to determine priority rankings. The results indicate that the Profile Matching-based decision support system provides more accurate and consistent recommendations compared to manual methods, while also improving the efficiency and transparency of the selection process for village authorities. Thus, the system has the potential to serve as an effective tool in ensuring that RUTILAHU assistance is properly targeted according to the needs of the Cijagra Paseh community.
Co-Authors Anwar, M. Taufan Anwar Anwar, Moch. Taufan Anwar, Moh. Taufan Atmoko, Dwi Dewi, Sofia Lusiana, Novita Naasyiah, Rifdah Nurmalasari, Evi Rachman, Tonton Taufik Ramdhani, M. Rizki Ramdhani Rifasya, Pramadika Salsabila, Jihan Salma Tina Rahmawati