Penerapan metode Multi-Objective Optimization on The Basis Of Simple Ratio Analysis dalam perangkingan siswa berprestasi
Keywords:
MOOSRA, decision support system (DSS), students performance in exams dataset, multi-criteria decision making (MCDM), student achievementAbstract
This study aims to apply the Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method to determine high-achieving students based on several academic criteria, namely math score, reading score, writing score, and test preparation course. The data used comes from the Students Performance in Exams Dataset with 10 student data as the research sample. The results show that alternative A7 obtained the highest preference value of 0.421, thus ranking first. Manual calculations and implementation using Python produced identical preference values and ranking order, thus indicating that the MOOSRA method is able to provide consistent, objective, and accurate results in the decision-making process. These findings indicate that the MOOSRA method can be used as a decision support system to assist schools in determining high-achieving students in a more transparent, efficient, and measurable manner. In addition, the application of this method has the potential to reduce subjectivity in the assessment process so that the resulting decisions are fairer and more accountable.
Downloads
References
Brauers, W. K., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 445–469.
Choridah, R. A., & Mufidah, N. (2024). Prestasi Mahasiswa dan Perbandingan Kurikulum 2013 Menjadi Kurikulum Merdeka. Jurnal Education and Development, 12(1), 125–131. https://repository.uin-malang.ac.id/18513/
Karim, A., Esabella, S., Andriani, T., & Hidayatullah, M. (2022). Penerapan Metode Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) dalam Penentuan Lulusan Mahasiswa Terbaik. Vol, 4, 162–168.
Lubis, J. H., Sanwani, S., Lubis, A., Mesran, M., Julaysa, J., & Hutapea, N. S. (2025). Decision Support System for Selecting the Best Head of Study Program Applying the Multi-Objective Optimization Method on the Basis of Simple Ratio Analysis (MOOSRA). Bulletin of Informatics and Data Science, 4(1), 53–61.
Narayanamoorthy, S., Annapoorani, V., Kang, D., Baleanu, D., Jeon, J., Kureethara, J. V., & Ramya, L. (2020). A novel assessment of bio-medical waste disposal methods using integrating weighting approach and hesitant fuzzy MOOSRA. Journal of Cleaner Production, 275, 122587.
Rizqi, S. A., Fachri, B., & Batubara, S. (2025). Penerapan Metode Moosra Untuk Evaluasi Kinerja Pengajar Di Ponpes Tahfidzul Qur’an Darul Iman Ar Ridho. Jurnal Komputer Teknologi Informasi Sistem Informasi (JUKTISI), 4(1), 359–367.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Renata Dwi Yasarah
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
