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All Journal JISA (Jurnal Informatika dan Sains) TIN: TERAPAN INFORMATIKA NUSANTARA
Oktavia, Petricia
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Analisis Komparatif Metode MOORA dan MAUT untuk Rekomendasi Pengangkatan Tenaga Pendidik Oktavia, Petricia; Frindo, Muhamad Meky
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7337

Abstract

The objective and data-driven recruitment of educators is a strategic step toward improving the quality of education. This study aims to develop a recommendation system for selecting prospective educators by comparing two multi-criteria decision-making methods: MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) and MAUT (Multi-Attribute Utility Theory). Five key criteria were used in the evaluation: Grade Point Average (GPA), mastery of didactic and methodological knowledge, teaching experience, age, and distance from home to school. Primary data were collected directly from educational institutions and prospective educators, involving six alternatives that were analyzed through normalization, weighting, and final score calculation. The analysis showed that the MOORA method identified candidate A2 as the best with a score of 0.3143, while the MAUT method ranked candidate A6 highest with a score of 0.644. The difference in rankings stems from the distinct evaluation principles of the two methods: MOORA relies on normalized ratios relative to the maximum value, while MAUT applies an aggregated utility approach. Despite this variation, both methods consistently identified the top three candidates. The developed recommendation system not only enhances transparency and accountability but also outperforms conventional intuition-based approaches by providing a structured, measurable, and replicable framework. This system has the potential to be adopted by educational institutions to ensure a fairer and more objective educator recruitment process.
Design and Construction of an System for Diagnosis of Online Game Addiction Using The Forward Chaining and Certainty Factor Methods Based on a Website (Case Study: RSU South Tangerang) Oktavia, Petricia; Ferdiansyah, Ferdiansyah
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2434

Abstract

 Online games are a type of game that provides a unique pleasure for players, as they can be played not only alone (singleplayer) but also with two or more people (multiplayer) from various locations and countries. Online games are a kind of game that gives players something special because they can be played either singleplayer or with two or more people from different places and countries. According to the APJII 2025 poll, 34.91% of participants spend one to two hours a day playing online games.  This suggests that playing online games has ingrained itself into people's daily lives.  Because of this, many people can become addicted to online games without realizing it. It might result in adverse bodily effects like exhaustion, weakened immunity, visual issues, anxiety, restlessness when not playing, diminished focus, and emotional shifts (irritability or sensitivity). Therefore, an expert system is needed to diagnose online game addiction as a means of determining the level of addiction. This website aims to determine the level of online game addiction, using the data and the forward chaining method, which aims to generate a conclusion from existing facts. With this method, a conclusion will be obtained, which is then further processed to determine the certainty value. And this expert system requires the certainty factor method to find this certainty value. Given the problems and needs at RSU Tangerang Selatan, this research has produced an expert system for diagnosing online game addiction, which provides ease of use because it is published on a website. This expert system generates output that includes conclusions based on existing facts, the level of online game addiction determined by the certainty factor method, a certainty value ranging from 0% to 100%, and solutions provided by experts.
Co-Authors Ferdiansyah Ferdiansyah Frindo, Muhamad Meky