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All Journal JUITA : Jurnal Informatika JIKO (Jurnal Informatika dan Komputer)
Sri Mulyana
Universitas Gadjah Mada
Computer Science & IT

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A Nonlinear Utility-Based GDSS Model for Village Development Priority Determination Ubaidilah Aminuddin Thoyieb; Dyah Aruming Tyas; Sri Mulyana
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 2, July 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v14i2.30656

Abstract

The determination of village development priorities through Village Development Planning Deliberation often faces subjectivity, limited analytical instruments, and difficulties in evaluating multiple alternatives and criteria simultaneously. Conventional approaches such as Simple Additive Weighing (SAW) and TOPSIS exhibit different characteristics in distinguishing alternatives with similar evaluation profiles. This study proposed a group decision support system model based on nonlinear utility for adaptive collective decision-making. The model integrated the Analytical Hierarchy Process (AHP) for sector weighing, the Simple Multi-Attribute Rating Technique (SMART) with nonlinear utility functions for alternative evaluation, and the Borda method for preference aggregation. The proposed model was compared with AHP–SAW–Borda and AHP–TOPSIS–Borda using a case study involving 24 development program alternatives classified into 5 development sectors and evaluated using 6 assessment parameters. The results showed that the proposed model maintained globally consistent ranking structures across both comparison approaches. Spearman correlation coefficients reached 0.9389 for SMART versus SAW and 0.9519 for SMART versus TOPSIS, indicating strong consistency across additive and distance-based evaluation paradigms. Ranking variations mainly occurred among mid-ranked alternatives, while dominant priorities remained stable. The findings indicate that nonlinear utility transformation improves adaptive ranking sensitivity while preserving overall decision stability.
Group Decision Support System (GDSS) Model on Software Engineer Selection: Integration of AHP,SAW, TOPSIS, and BORDA Tika Novita Sari; Ria Astriratma; Sri Mulyana
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 1 (2025): Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i1.1495

Abstract

One of the requirements for any company's success is the efficient utilization of human resources in its operations. There are several different tasks that fall within the Human Resources Management (HRM) role. This study uses the GDSS technique, combining TOPSIS for the second decision maker and AHP-SAW for the first decision maker. There are two decision makers (DMs), as is the case. After that, each decision maker's ranking will be processed using the BORDA technique. This study concludes that there are differences in the outcomes from DM1 and DM2. This is a result of the propensity for every decision-maker to offer a unique assessment. While DM2 employs the scoring technique using percentages to determine sub-parameter weighting and the TOPSIS method for ranking, DM1 uses the AHP method for sub-parameter weighting and SAW for ranking. However, the researchers integrated the two decision makers with a group decision support system utilizing the BORDA approach, accounting for the decision makers' respective levels of interest. The findings highlight the significant contribution of this research in demonstrating how the integration of these methods effectively addresses differences in evaluation approaches among decision-makers, particularly in the context of software engineering, ensuring a transparent and data-driven selection process. The GDSS model was tested on a case study of software engineer selection, demonstrating a high level of accuracy in identifying the most suitable candidates for organizational needs. Furthermore, the results of the GDSS aligned with the decisions made by the case study company, validating the effectiveness of the proposed model. The practical application of this model can be adopted by companies to enhance the efficiency and quality of recruitment processes.
Co-Authors Dyah Aruming Tyas Ria Astriratma Tika Novita Sari Ubaidilah Aminuddin Thoyieb