Web-Based Decision Support System for Selecting Exemplary Teachers usingTOPSIS Method

Authors

  • Sumardiono Sumardiono Bina Insani University http://orcid.org/0000-0002-4770-9821
  • Norhafizah Ismail Politeknik Mersing Johor
  • Jafar Shadiq Bina Insani University
  • Zahra Qotrun Nida Bina Insani University
  • Solikin Solikin Bina Insani University
  • Riska Suryani Universitas Harapan Bangsa

DOI:

https://doi.org/10.15408/aism.v8i1.45488

Keywords:

Decision Support System, TOPSIS Algorithm, Exemplary Teachers, Teacher Selection, Vocational School

Abstract

This study creates an online Decision Support System (DSS) using the TOPSIS algorithm to fairly choose outstanding teachers from vocational schools in Bekasi City, which has 87 state and private vocational secondary schools with about 62,000 students. To tackle the current biased selection process, our research uses a multi-criteria approach that looks at discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). Targeting this substantial educational population, our research addresses the current subjective selection process by implementing a multi-criteria approach evaluating discipline (25%), travel costs (20%), personality (20%), teaching administration (15%), and learning achievements (20%). The TOPSIS method was selected for its proven effectiveness in ranking alternatives based on geometric distance from ideal solutions, particularly valuable in large-scale educational contexts. Analysis of 14 teacher candidates from SMK Bina Karya Mandiri demonstrated the system's precision, with Didi Saputra, S.Pdi, emerging as top-ranked (preference value: 0.63). When extrapolated to Bekasi's 87 SMKs, the model shows potential to standardize teacher assessment citywide, reducing regional disparities in recognition practices. The web-based platform enhances accessibility, allowing principals across 21 sub-districts to input localized data while maintaining centralized benchmarking. Key findings reveal (1) discipline and personality collectively account for 45% of exemplary status determination, (2) cost-related factors show inverse correlation with remote school nominations, and (3) system implementation could reduce selection time by ≈68% compared to manual methods. This study contributes both a scalable framework for educational DSS and empirical data on vocational teacher excellence criteria in urban Indonesia.

Downloads

Download data is not yet available.

References

R. R. S. and D. Naibaho, “Function of Schools,” PediaquJurnal Pendidik. Sos. dan Hum., vol. 13, no. 1, pp. 104–116, 2023.

N. Neliwati, Z. Surion2, R. Rinald, and Y. Tamiang, “Decision Making and Improving the Quality of Education at SMK Negeri 2 Binjai,” J. Guru Kita PGSD, vol. 6, no. 2, p. 169, 2022, doi: 10.24114/jgk.v6i2.31650.

J. Khoirunnisa Anggraini and M. Orisa, “Sistem Pendukung Keputusan Pemilihan Guru Terbaik Dengan Metode Topsis Berbasis Web (Studi Kasus Sman 1 Kuaro),” JATI (Jurnal Mhs. Tek. Inform., vol. 6, no. 2, pp. 1009–1015, 2023, doi: 10.36040/jati.v6i2.5422.

L. H. Marwa Sulehu, “Sistem Pendukung Keputusan Penilaian Desa Terbaik Menggunakan Metode Additive Ratio Assessment (Aras),” Simtek J. Sist. Inf. dan Tek. Komput., vol. 4, no. 1, pp. 32–39, 2019, doi: 10.51876/simtek.v4i1.42.

P. Gayatri, H. Ruminar, and A. P. Lintangsari, “Students’ perceptions of an exemplary online esp teacher: a mixed-methods study,” Inspiring English Educ. J., vol. 7, no. 2, pp. 300–323, 2024.

L. T. Saaty, “Competitive priorities and knowledge management: An empirical investigation of manufacturing companies in UAE,” J. Manuf. Technol. Manag., vol. 26, no. 6, pp. 791–806, 2015, doi: 10.1108/JMTM-03-2014-0020.

S. Nasirin, I. A. A. Bahar, N. Mohd. Tuah, A. Kadir, C. Salimun, and S. Yussof, “Examining Decision Support Systems (DSS) Verification Approaches of the Government Agencies in East Malaysia,” Procedia Comput. Sci., vol. 234, no. 2023, pp. 1546–1552, 2024, doi: 10.1016/j.procs.2024.03.156.

D. Yuliana, F. Ayu, I. Mas’ud, F. Hidayat, and S. Alfadri, “Application of Decision Support System for Employee’S Bonus Using Analytical Hierarchy Process Method,” J. Appl. Eng. Technol. Sci., vol. 4, no. 1, pp. 441–450, 2022, doi: 10.37385/jaets.v4i1.1181.

M. Paul, N. Reinbold, M. Paul, N. Reinbold, C. Ortiz, and G. Reinhart, “ScienceDirect ScienceDirect Decision-support system for automotive recycling : disassembling Decision-support system for automotive recycling : disassembling components before shredding ? components before shredding ?,” Procedia Comput. Sci., vol. 253, no. 2024, pp. 465–474, 2025, doi: 10.1016/j.procs.2025.01.108.

P. Agyemang, E. M. Kwofie, J. I. Baum, D. Wang, and E. A. Kwofie, “Environmental-Health Convergence: A deep learning-oriented decision support system for catalyzing sustainable healthy food systems,” Environ. Model. Softw., vol. 185, no. December 2024, p. 106309, 2025, doi: 10.1016/j.envsoft.2024.106309.

G. Wen and F. Ji, “Flood resilience assessment of region based on TOPSIS-BOA-RF integrated model,” Ecol. Indic., vol. 169, no. November, p. 112901, 2024, doi: 10.1016/j.ecolind.2024.112901.

G. Anand, S. Sardar, S. Sah, A. Guha, and D. Das, “Multi-objective optimization to enhance surface integrity in WEDM for Al-matrix composite : A comparative assessment of self-weight adjusting MCDMs and objective weight integrated hybrid TOPSIS methods,” Results in Surfaces and Interfaces, vol. 18, no. February, p. 100467, 2025, doi: 10.1016/j.rsurfi.2025.100467.

J. Barman, B. Biswas, S. S. Ali, and M. Zhran, “The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS,” MethodsX, vol. 13, no. October, 2024, doi: 10.1016/j.mex.2024.103005.

C. D. Petru, R. E. Breaz, S. G. Racz, M. Crenganis, C. E. Gîrjob, and P. Drasovean, “Decision support methodology for the selection of industrial robots using BWM and TOPSIS methods,” Procedia Comput. Sci., vol. 242, pp. 43–50, 2024, doi: 10.1016/j.procs.2024.08.227.

B. Simamora, “Skala Likert, Bias Penggunaan dan Jalan Keluarnya,” J. Manaj., vol. 12, no. 1, pp. 84–93, 2022, doi: 10.46806/jman.v12i1.978.

R. A. Malik, S. M. Octafia, and V. S. Gunawan, “Easily Determining Post-Study System Usability for Anime Community E-Commerce Analysis,” vol. 7, no. 2, pp. 39–44, 2024, doi: 10.15408/aism.v7i2.39352.

R. A. Ayinselya, “Teachers’ sense of professional identity in Ghana: listening to selected teachers in rural Northern Ghana,” Practice, vol. 2, no. 2, pp. 110–127, 2020, doi: 10.1080/25783858.2020.1831736.

N. Ezhilarasan and C. Vijayalakshmi, “Optimization of Fuzzy programming with TOPSIS Algorithm,” Procedia Comput. Sci., vol. 172, pp. 473–479, 2020, doi: 10.1016/j.procs.2020.05.144.

M. Madanchian and H. Taherdoost, “A comprehensive guide to the TOPSIS method for multi-criteria decision making,” Sustain. Soc. Dev., vol. 1, no. 1, pp. 1–6, 2023, doi: 10.54517/ssd.v1i1.2220.

M. A. G. Fonseca, L. S. De Faria, and S. R. Lourenço, “Original Research Article Original Research Article Open Access Selection of Energy Efficiency Industrial Projects Using Topsis Method,” Int. J. Dev. Res., vol. 09, no. 03, pp. 26719–26724, 2019.

V. M. M. Siregar, S. Sonang, A. T. Purba, H. Sugara, and N. F. Siagian, “Implementation of TOPSIS Algorithm for Selection of Prominent Student Class,” J. Phys. Conf. Ser., vol. 1783, no. 1, 2021, doi: 10.1088/1742-6596/1783/1/012038.

H. S. K. Veguru, J. Naren, and Y. Singam, “Student’s Interest and Opinion Towards Online Education,” Procedia Comput. Sci., vol. 233, pp. 590–596, 2024, doi: 10.1016/j.procs.2024.03.248.

S. Sauda and E. P. Agustini, “Implementasi Prototype Model dalam Pengembangan Aplikasi Smart Cleaning Sebagai Pendukung Aplikasi Smart City,” MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput., vol. 20, no. 1, pp. 73–84, 2020, doi: 10.30812/matrik.v20i1.673.

K. Kurniati, “Penerapan Metode Prototype Pada Perancangan Sistem Pengarsipan Dokumen Kantor Kecamatan Lais,” J. Softw. Eng. Ampera, vol. 2, no. 1, pp. 16–27, 2021, doi: 10.51519/journalsea.v2i1.89.

Sumardiono, “PERANCANGAN SISTEM PENILAIAN (E-RESULT) PEGAWAI DENGAN MODEL WATERFALL DI UNIVERSITAS XYZ,” TEKNOSAINS J. Sains, Teknol. dan Inform., vol. 8, no. 1, pp. 45–53, Jan. 2021, doi: 10.37373/tekno.v8i1.76.

T. Tuslaela, “the Scholarship Awarding Decision Support System Uses the Topsis Method,” J. Ris. Inform., vol. 2, no. 4, pp. 201–206, 2020, doi: 10.34288/jri.v2i4.154.

J. A. Q. Salibat and R. L. Genuba, “Exemplary Teacher Characteristics, Interpersonal Reactivity, and Organizational Climate: A Causal Model on Keeping Quality Teachers in Private Educational Institutions,” Int. J. Multidiscip. Res., vol. 6, no. 4, pp. 1–29, 2024, doi: 10.36948/ijfmr.2024.v06i04.25767.

L. Bardach, J. V. Rushby, L. E. Kim, and R. M. Klassen, “Using video- and text-based situational judgement tests for teacher selection: a quasi-experiment exploring the relations between test format, subgroup differences, and applicant reactions,” Eur. J. Work Organ. Psychol., vol. 30, no. 2, pp. 251–264, 2021, doi: 10.1080/1359432X.2020.1736619.

Downloads

Published

2025-05-31

How to Cite

Web-Based Decision Support System for Selecting Exemplary Teachers usingTOPSIS Method. (2025). Applied Information System and Management (AISM), 8(1), 89-94. https://doi.org/10.15408/aism.v8i1.45488