Development of a Multi-Criteria Decision Support System for Scholarship Selection Based on the Analytical Hierarchy Process (AHP) Method
DOI:
https://doi.org/10.24036/jteki.v1i1.1Keywords:
Decision Support System, Analytical Hierarchy Process, Scholarship Selection, Web-Based Application, Multi-Criteria Decision Making, Educational TechnologyAbstract
Ensuring fairness and consistency in scholarship selection remains a major challenge, particularly in institutions serving underprivileged students. Conventional decision-making methods are often subjective and lack standardized evaluation criteria, leading to inconsistent outcomes. This study proposes a web-based Decision Support System (DSS) integrated with the Analytic Hierarchy Process (AHP) to enhance the objectivity, transparency, and efficiency of scholarship selection. The AHP method enables stakeholders to perform structured pairwise comparisons of selection criteria, calculate consistency ratios, and generate priority weights to rank candidates objectively. The system was developed using PHP and MySQL, and designed via a modular MVC architecture. A case study involving 45 applicants across three vocational high schools in Padang, Indonesia, was conducted using five criteria: academic performance, parental income, number of dependents, extracurricular achievements, and student organization involvement. Evaluation results show that the system reduced processing time by 38%, improved ranking consistency, and increased stakeholder satisfaction based on survey feedback. The system’s centralized, web-based nature also facilitates data sharing between schools and education authorities. Despite its benefits, limitations include the use of static weight configurations and restricted institutional coverage. Future work will focus on incorporating adaptive decision models and expanding implementation across a wider educational context to support policy-driven flexibility.
Downloads
References
[1] Z. Jahantab, “Role of Education in National Development,” Pakistani J. Appl. Soc. Sci., vol. 12, no. 1, pp. 87–108, Mar. 2021, https://doi.org/10.46568/PJASS.V12I1.543.
[2] C. Peercy and N. Svenson, “The role of higher education in equitable human development,” Int. Rev. Educ., vol. 62, no. 2, pp. 139–160, Apr. 2016, https://doi.org/10.1007/s11159-016-9549-6.
[3] A. V. Agbedahin, “Sustainable development, Education for Sustainable Development, and the 2030 Agenda for Sustainable Development: Emergence, efficacy, eminence, and future,” Sustain. Dev., vol. 27, no. 4, pp. 669–680, Jul. 2019, https://doi.org/10.1002/sd.1931.
[4] E. P. St. John, M. S. McPherson, and M. O. Schapiro, “The Student Aid Game: Meeting Need and Rewarding Talent in American Higher Education,” J. Higher Educ., vol. 69, no. 5, p. 577, 1998, https://doi.org/10.2307/2649111.
[5] G. A. Berg, “Low-Income Students and the Perpetuation of Inequality: Higher Education in America,” Low-Income Students Perpetuation Inequal. High. Educ. Am., pp. 1–212, Jan. 2016, https://doi.org/10.4324/9781315593067.
[6] S. Marginson, “Limitations of human capital theory*,” Stud. High. Educ., vol. 44, no. 2, pp. 287–301, Feb. 2019, https://doi.org/10.1080/03075079.2017.1359823.
[7] C. Eesley, “Institutional barriers to growth: Entrepreneurship, human capital and institutional change,” Organ. Sci., vol. 27, no. 5, pp. 1290–1306, Sep. 2016, https://doi.org/10.1287/orsc.2016.1077.
[8] R. J. Reed and B. Hurd, “A value beyond money? Assessing the impact of equity scholarships: from access to success,” Stud. High. Educ., vol. 41, no. 7, pp. 1236–1250, Jul. 2016, https://doi.org/10.1080/03075079.2014.968541.
[9] C. Cosentino, J. Fortson, S. Liuzzi, A. Harris, and R. Blair, “Can scholarships provide equitable access to high-quality university education? Evidence from the Mastercard Foundation Scholars Program,” Int. J. Educ. Dev., vol. 71, p. 102089, Nov. 2019, https://doi.org/10.1016/j.ijedudev.2019.102089.
[10] N. Zacharias and J. Ryan, “Moving beyond ‘acts of faith’: effective scholarships for equity students,” J. High. Educ. Policy Manag., vol. 43, no. 2, pp. 147–165, Mar. 2021, https://doi.org/10.1080/1360080X.2020.1777499.
[11] A. Ghaicha, “Theoretical Framework for Educational Assessment: A Synoptic Review,” J. Educ. Pract., vol. 7, no. 24, pp. 212–231, 2016, Accessed: Jul. 13, 2021. [Online]. Available: www.iiste.org.
[12] C. Pretorius, “Exploring procedural decision support systems for wicked problem resolution,” South African Comput. J., vol. 29, no. 1, pp. 191–219, 2017, https://doi.org/10.18489/sacj.v29i1.448.
[13] K. L. Mosier and U. M. Fischer, “Judgment and decision making by individuals and teams: Issues, models, and applications,” Decis. Mak. Aviat., pp. 139–197, Jul. 2017, https://doi.org/10.1518/155723410x12849346788822.
[14] M. W. L. Moreira, J. J. P. C. Rodrigues, V. Korotaev, J. Al-Muhtadi, and N. Kumar, “A Comprehensive Review on Smart Decision Support Systems for Health Care,” IEEE Syst. J., vol. 13, no. 3, pp. 3536–3545, Sep. 2019, https://doi.org/10.1109/JSYST.2018.2890121.
[15] P. B. Keenan and P. Jankowski, “Spatial Decision Support Systems: Three decades on,” Decis. Support Syst., vol. 116, pp. 64–76, Jan. 2019, https://doi.org/10.1016/j.dss.2018.10.010.
[16] A. Yahyaoui, A. Jamil, J. Rasheed, and M. Yesiltepe, “A Decision Support System for Diabetes Prediction Using Machine Learning and Deep Learning Techniques,” 1st Int. Informatics Softw. Eng. Conf. Innov. Technol. Digit. Transform. IISEC 2019 - Proc., Nov. 2019, https://doi.org/10.1109/UBMYK48245.2019.8965556.
[17] M. Tahvildarzadeh, H. Moghaddasi, and M. Hosseini, “A Framework for Quality Management of University Educational Information: A Review Study,” Res. Dev. Med. Educ., vol. 6, no. 1, pp. 3–11, Jun. 2017, https://doi.org/10.15171/rdme.2017.002.
[18] J. C. Huang, H. C. Huang, and S. H. Chu, “Research on image quality in decision management system and information system framework,” J. Vis. Commun. Image Represent., vol. 63, p. 102588, Aug. 2019, https://doi.org/10.1016/j.jvcir.2019.102588.
[19] H. U. Rahman, M. Raza, P. Afsar, A. Alharbi, S. Ahmad, and H. Alyami, “Multi-Criteria Decision Making Model for Application Maintenance Offshoring Using Analytic Hierarchy Process,” Appl. Sci. 2021, Vol. 11, Page 8550, vol. 11, no. 18, p. 8550, Sep. 2021, https://doi.org/10.3390/APP11188550.
[20] M. A. B. Promentilla, K. B. Aviso, R. I. G. Lucas, L. F. Razon, and R. R. Tan, “Teaching Analytic Hierarchy Process (AHP) in undergraduate chemical engineering courses,” Educ. Chem. Eng., vol. 23, pp. 34–41, Apr. 2018, https://doi.org/10.1016/j.ece.2018.05.002.
[21] A. Baumber, G. Metternicht, P. Ampt, R. Cross, and E. Berry, “Opportunities for adaptive online collaboration to enhance rural land management,” J. Environ. Manage., vol. 219, pp. 28–36, Aug. 2018, https://doi.org/10.1016/j.jenvman.2018.04.114.
[22] D. Ürer Erdil, M. Tümer, H. Nadiri, and I. Aghaei, “Prioritizing Information Sources and Requirements in Students’ Choice of Higher Education Destination: Using AHP Analysis,” SAGE Open, vol. 11, no. 2, 2021, https://doi.org/10.1177/21582440211015685.
[23] A. Darko, A. P. C. Chan, E. E. Ameyaw, E. K. Owusu, E. Pärn, and D. J. Edwards, “Review of application of analytic hierarchy process (AHP) in construction,” Int. J. Constr. Manag., vol. 19, no. 5, pp. 436–452, Sep. 2019, https://doi.org/10.1080/15623599.2018.1452098.
[24] I. Canco, D. Kruja, and T. Iancu, “Ahp, a reliable method for quality decision making: A case study in business,” Sustain., vol. 13, no. 24, p. 13932, Dec. 2021, https://doi.org/10.3390/su132413932.
[25] L. Chazette and K. Schneider, “Explainability as a non-functional requirement: challenges and recommendations,” Requir. Eng., vol. 25, no. 4, pp. 493–514, Dec. 2020, https://doi.org/10.1007/S00766-020-00333-1.
[26] N. Zanjani, S. L. Edwards, S. Nykvist, and S. Geva, “The important elements of LMS design that affect user engagement with e-learning tools within LMSs in the higher education sector,” Australas. J. Educ. Technol., vol. 33, no. 1, pp. 19–31, Apr. 2017, https://doi.org/10.14742/ajet.2938.
[27] A. Gharaibeh et al., “Smart Cities: A Survey on Data Management, Security, and Enabling Technologies,” IEEE Commun. Surv. Tutorials, vol. 19, no. 4, pp. 2456–2501, Oct. 2017, https://doi.org/10.1109/COMST.2017.2736886.
[28] S. Ray and M. Saeed, “Applications of educational data mining and learning analytics tools in handling big data in higher education,” Appl. Big Data Anal. Trends, Issues, Challenges, pp. 135–160, Jul. 2018, https://doi.org/10.1007/978-3-319-76472-6_7.
[29] R. T. Sutton, D. Pincock, D. C. Baumgart, D. C. Sadowski, R. N. Fedorak, and K. I. Kroeker, “An overview of clinical decision support systems: benefits, risks, and strategies for success,” npj Digit. Med., vol. 3, no. 1, pp. 1–10, Dec. 2020, https://doi.org/10.1038/s41746-020-0221-y.
[30] F. Sgarbossa, E. H. Grosse, W. P. Neumann, D. Battini, and C. H. Glock, “Human factors in production and logistics systems of the future,” Annu. Rev. Control, vol. 49, pp. 295–305, Jan. 2020, https://doi.org/10.1016/j.arcontrol.2020.04.007.
[31] H. Lau, Y. P. Tsang, D. Nakandala, and C. K. M. Lee, “Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology,” Ind. Manag. Data Syst., vol. 121, no. 7, pp. 1684–1703, 2021, https://doi.org/10.1108/IMDS-04-2020-0199.
[32] Z. Wurtzebach and C. Schultz, “Measuring Ecological Integrity: History, Practical Applications, and Research Opportunities,” Bioscience, vol. 66, no. 6, pp. 446–457, Jun. 2016, https://doi.org/10.1093/biosci/biw037.
[33] S. Sun, X. Zheng, J. Villalba-Díez, and J. Ordieres-Meré, “Data handling in industry 4.0: Interoperability based on distributed ledger technology,” Sensors (Switzerland), vol. 20, no. 11, p. 3046, May 2020, https://doi.org/10.3390/s20113046.
[34] K. Reddy Gade, “Data-Driven Decision Making in a Complex World,” J. Comput. Innov., vol. 1, no. 1, Feb. 2021, Accessed: Jul. 13, 2021. [Online]. Available: https://researchworkx.com/index.php/jciVo11.
[35] R. Matheus, M. Janssen, and D. Maheshwari, “Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities,” Gov. Inf. Q., vol. 37, no. 3, p. 101284, Jul. 2020, https://doi.org/10.1016/j.giq.2018.01.006.
[36] A. Farahzadi, P. Shams, J. Rezazadeh, and R. Farahbakhsh, “Middleware technologies for cloud of things: a survey,” Digit. Commun. Networks, vol. 4, no. 3, pp. 176–188, Aug. 2018, https://doi.org/10.1016/j.dcan.2017.04.005.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Viranti Fajri, Muhammad Anwar
This work is licensed under a Creative Commons Attribution 4.0 International License.
Alamat Redaksi :