Subjectivity Tracking System for Poor Scholarship Recipients at Elementary School Using the MOORA Method

Authors

  • Tundo Tundo Departement of Science Data, Universitas Putra Bangsa

DOI:

https://doi.org/10.31764/jtam.v6i3.8373

Keywords:

Poor Student Assistance, MOORA, Elementary School, Subjectivity,

Abstract

This research was conducted because of complaints from several parents at Elementary School regarding recipients of the Poor Student Assistance (PSA) who were still less objective. Elementary School XY regularly conduct screening activities every year to select prospective PSA recipients. This selection is made so that the recipients of this assistance are students entitled to it. Some students should be accepted as a selection committee but do not mistake of choosing some students who have kinship or subjective matters. Therefore, this study aims to explore and create applications that apply the Multi Objective Optimization to the basic  Ratio Analysis (MOORA) method, which is a method for determining students based on predetermined criteria. The criteria used are the value of report cards, student achievement, student activity, parental income, parental dependents, and home conditions. After conducting a search and implementation using the MOORA method in determining PSA recipients, it was found that there were some non-objective results where the student's criteria and final results were lower than some other students. However the Elementary School provided a recommendation to get PSA. If this happens again, then the importance of this system is to help objective selection. The accuracy results explained that 14.39% of PSA recipients were subjective. It was concluded that this research helps an objective decision and facilitates the decision maker in determining the best 3 recipients from each class at Elementary School XY.

References

Akbar, R., & ’Uyun, S. (2021). Penentuan Bantuan Siswa Miskin Menggunakan Fuzzy Tsukamoto Dengan Perbandingan Rule Pakar dan Decision Tree (Studi Kasus : SDN 37 Bengkulu Selatan). Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(4), 651. https://doi.org/10.25126/jtiik.0813191

Assrani, D., Huda, N., Sidabutar, R., Saputra, I., & Sulaiman, O. K. (2018). Penentuan Penerima Bantuan Siswa Miskin Menerapkan Metode Multi Objective Optimization on The Basis of Ratio Analysis (MOORA). JURIKOM (Jurnal Riset Komputer), 5(1), 1–5.

Brauers, W. K. M. (2018). Location theory and multi-criteria decision making: An application of the MOORA method. Contemporary Economics, 12(3), 241–252. https://doi.org/10.5709/ce.1897-9254.275

Deniz Basar, O., & Guneren Genc, E. (2019). Comparison of Country Ratings of Credit Rating Agencies with MOORA Method. Business and Economics Research Journal, 10(2), 391–404. https://doi.org/10.20409/berj.2019.175

Fedajev, A., Stanujkic, D., Karabašević, D., Brauers, W. K. M., & Zavadskas, E. K. (2020). Assessment of progress towards “Europe 2020†strategy targets by using the MULTIMOORA method and the Shannon Entropy Index. Journal of Cleaner Production, 244. https://doi.org/10.1016/j.jclepro.2019.118895

Gou, X., Liao, H., Xu, Z., & Herrera, F. (2017). Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures. Information Fusion, 38(February), 22–34. https://doi.org/10.1016/j.inffus.2017.02.008

Gurbuz, F., & Erdinc, G. (2018). Selecting the Best Hotel Using the Fuzzy-Moora Method with a New Combined Weight Approach. ISMSIT 2018 - 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings, 1–8. https://doi.org/10.1109/ISMSIT.2018.8566688

Hafezalkotob, A., Hafezalkotob, A., Liao, H., & Herrera, F. (2019). An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges. Information Fusion, 51, 145–177. https://doi.org/10.1016/j.inffus.2018.12.002

Handayani, R. I., Triningsih, T., & Putri, M. (2020). Decision Support System for Achieving Scholarship Selection by Using Profile Matching Method. SinkrOn, 4(2), 92. https://doi.org/10.33395/sinkron.v4i2.10530

Manurung, S., Simamora, I. M. S., & Allagan, H. (2021). Comparison of Moora , Waspas and SAW Methods in Decision Support Systems. Jurnal Mantik, 5(36), 485–493.

Pane, D. H., & Erwansyah, K. (2020). Model Prioritas Pemilihan Daerah Pembangunan Tower Telekomunikasi Berbasis Kombinasi Metode AHP dan Metode Moora. Jutisi, 9(2), 11–22.

Prasad, K., & Sekar. (2016). Optimal Alternative Selection Using MOORA in Industrial Sector - A. International Journal of Fuzzy Logic Systems, 6(2), 01–21. https://doi.org/10.5121/ijfls.2016.6201

Siahaan, A. P. U., Rahim, R., & Mesran, M. (2017). Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis. International Seminar: Research for Science, Technology AND Culture (IRSTC 2017). https://doi.org/10.31219/osf.io/cwfpu

Sinaga, D. C. P., Marpaung, P., & Sianipar, B. (2021). The Application of the MOORA Method in the Decision Making System for the Selection of the Best Employees at CV. Lautan Mas. IJISTECH (International Journal of Information System & Technology), 5(2), 233–239.

Singh, B. (2017). Applications of MOORA method for benchmarking decision in Indian industries. International Journal of Advanced Operations Management, 9(2), 88–105. https://doi.org/10.1504/IJAOM.2017.086674

Siregar, M. U., Nasiroh, T., & Mustakim, M. (2021). Suatu Pendekatan Hibrid Menggunakan Topsis-Entropi pada Kriteria Objektif A Hybrid Approach Using Entropy-Topsis to Determine Merit Scholars Based on Objective Criteria. Jurnal Teknologi Informasi dan Ilmu Komputer, 8(1), 167–176. https://doi.org/10.25126/jtiik.202184261

Sugiyarto, S., Eliyanto, J., Irsalinda, N., Putri, Z., & Fitrianawat, M. (2021). A Fuzzy Logic in Election Sentiment Analysis: Comparison Between Fuzzy Naïve Bayes and Fuzzy Sentiment using CNN. JTAM (Jurnal Teori Dan Aplikasi Matematika), 5(1), 110. https://doi.org/10.31764/jtam.v5i1.3766

Trung, D. D., Quang, N. H., Lam, P. D., Linh, N. H., Lam, L. Q., Hung, L. X., & Tuan, N. A. (2021). Combination of taguchi method and moora method for multi-objective optimization of SCM400 steel milling process. E3S Web of Conferences, 309, 01092. https://doi.org/10.1051/e3sconf/202130901092

Tundo, & Sela, E. I. (2018). Application of the Fuzzy Inference System Method to Predict the Number of Weaving Fabric Production. (IJID) International Journal on Informatics for Development, 7(1), 1–9.

Tundo, T., & Kurniawan, D. (2019). Implementation of the Weighted Aggregated Sum Product Assesment Method in Determining the Best Rice for Serabi Cake Making. IJID (International Journal on Informatics for Development), 8(1), 40. https://doi.org/10.14421/ijid.2019.08107

Zaitun, Z., Mustakim, Kamila, I., & Helma, S. S. (2019). Implementation of MOORA Method for Determining Prospective Smart Indonesia Program Funds Recipients. International Journal of Engineering and Advanced Technology, 9(2), 1922–1925. https://doi.org/10.35940/ijeat.b2860.129219

Published

2022-07-16

Issue

Section

Articles