Application of Fuzzy Analytical Hierarchy Process (FAHP) in the selection of study space
DOI:
https://doi.org/10.55573/JISED.118773Keywords:
Fuzzy Analytical Hierarchy Process (FAHP), ulti-Criteria Decision Making (MCDM), Study Space Selection, Higher Education, Learning EnvironmentAbstract
A study space is a location or environment used by a person to carry out learning activities. It can include various places such as bedrooms, libraries, cafes, dormitories, or any place that is suitable for a person to focus on studies. A suitable study space can contribute to the effectiveness of the learning process. Choosing a suitable study space is very important, especially for university students who often face various challenges every semester such as assignments, exams, and presentations. This research introduces a Fuzzy Analytical Hierarchy Process (FAHP) approach to determine the most important criteria and rank four study spaces which are library, study lounges, outdoor study spot, and dormitory rooms among students in Universiti Teknologi MARA Kelantan Branch (UiTMCK). This study was rated for criteria and alternatives by five decision makers using a linguistic scale. The evaluation was conducted based on four main criteria and alternatives. Among the criteria, environmental conditions (C1) have been identified as the most influential criterion. Meanwhile, the most preferred study space by students is Library (A1), This research shows the importance of FAHP in resolving complex problems in decision making and supports the formation of a productive and consistent learning routine. For future study, the FAHP can be applied to other fields and combined with other uncertainty theories.
Downloads
References
Afolayan, A., Ojokoh, B., & Adetunmbi, A. (2020). Performance analysis of fuzzy analytic hierarchy process multi-criteria decision support models for contractor selection. Scientific African, 9, e00471. https://doi.org/10.1016/j.sciaf.2020.e00471
Aliyev, R., Temizkan, H., & Aliyev, R. (2020). Fuzzy analytic hierarchy process-based multi-criteria decision making for universities ranking. Symmetry, 12(8), 1351. https://doi.org/10.3390/sym12081351
Alwedyan, S. (2024). Optimal location selection of a casual-dining restaurant using a multi-criteria decision-making (MCDM) approach. International Journal for Spatial Planning and Sustainable Development, 12(1), 156–172. https://doi.org/10.14246/irspsd.12.1156
Ashrafzadeh, M., Rafiei, F. M., Isfahani, N. M., & Zare, Z. (2012). Application of fuzzy TOPSIS method for the selection of warehouse location: A case study. Interdisciplinary Journal of Contemporary Research in Business, 3(9), 655–671.
Beckers, R., van der Voordt, T., & Dewulf, G. (2016). Learning space preferences of higher education students. Building and Environment, 104, 243–252. https://doi.org/10.1016/j.buildenv.2016.05.013
Berry, C. M., Ones, D. S., & Sackett, P. R. (2002). Interpersonal deviance, organizational deviance, and their common correlates: A review and meta-analysis. Journal of Applied Psychology, 92(2), 410. https://doi.org/10.1037/0021-9010.92.2.410
Biswas, A., Gazi, K. H., Sankar, P. M., & Ghosh, A. (2025). A decision-making framework for sustainable highway restaurant site selection: AHP-TOPSIS approach based on the fuzzy numbers. Spectrum of Operational Research, 2(1), 1–26. https://doi.org/10.56578/sor020101
Castro, F., et al. (2013). Indoor environmental quality and layout for sustainable healthcare design. In A conceptual framework for sustainable evidence-based design.
Chan, H. K., Sun, X., & Chung, S.-H. (2019). When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 125, 113114. https://doi.org/10.1016/j.dss.2019.113114
Davies, M. A. (1994). A multicriteria decision model application for managing group decisions. Journal of the Operational Research Society, 45(1), 47–58. https://doi.org/10.1057/jors.1994.6
Harrop, D., & Turpin, B. (2013). A study exploring learners’ informal learning space behaviors, attitudes, and preferences. New Review of Academic Librarianship, 19(1), 58–77. https://doi.org/10.1080/13614533.2013.740961
Helbich, M., Klein, N., Roberts, H., et al. (2018). More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach. arXiv preprint arXiv:1809.00123. https://doi.org/10.48550/arXiv.1809.00123
Jusoh, R., & Parnell, J. A. (2005). Competitive strategy and performance measurement in the Malaysian context: An exploratory study. Management Decision, 46(1), 5–31. https://doi.org/10.1108/00251740810846716
Köksalan, M., Wallenius, J., & Zionts, S. (2013). An early history of multiple criteria decision making. Journal of Multi-Criteria Decision Analysis, 20(1-2), 87–94. https://doi.org/10.1002/mcda.1481
Lau, S. S. Y., & Yang, F. (2009). Introducing healing gardens into a compact university campus: Design natural space to create healthy and sustainable campuses. Landscape Research, 34(1), 55–81. https://doi.org/10.1080/01426390802591483
Lin, H.-F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877–888. https://doi.org/10.1016/j.compedu.2009.09.017
Liu, Y., Eckert, C., & Earl, C. (2020). A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, 113738. https://doi.org/10.1016/j.eswa.2020.113738
Mahad, N. F., Yusof, N., & Ismail, N. F. (2019). The application of fuzzy analytic hierarchy process (FAHP) approach to solve multi-criteria decision making (MCDM) problems. Journal of Physics: Conference Series, 1358. https://doi.org/10.1088/1742-6596/1358/1/012081
Mrinmoy, S., & Majumder, M. (2015). Multi criteria decision making. In Impact of Urbanization on Water Shortage in Face of Climatic Aberrations (pp. 35–47). Springer. https://doi.org/10.1007/978-981-287-414-6_4
Nguyen, N., Lin, G., & Dang, T. (2021). Fuzzy multi-criteria decision making approach for online food delivery (OFD) companies evaluation and selection: A case study in Vietnam. Processes, 9(7), 1274. https://doi.org/10.3390/pr9071274
Read, J., & Meath, C. (2025). A conceptual framework for sustainable evidence-based design for aligning therapeutic and sustainability outcomes in healthcare facilities: A systematic literature review. HERD: Health Environments Research & Design Journal. https://doi.org/10.1177/19375867241234567
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill.
Saaty, T. L. (2004). Decision making—the analytic hierarchy and network processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1–35. https://doi.org/10.1007/s11518-006-0151-5
Saaty, T. L. (2005). Theory and applications of the analytic network process: Decision making with benefits, opportunities, costs, and risks. RWS Publications.
Şahin, R., & Yiğider, M. (2014). A multi-criteria neutrosophic group decision making method based on TOPSIS for supplier selection. arXiv preprint arXiv:1412.5077. https://doi.org/10.48550/arXiv.1412.5077
Sonmez Gumushan, Y., & Sonmez Cakir, F. (2023). Ranking the criteria effective in the selection of e-learning system by fuzzy AHP (F-AHP) method. Journal of Theoretical Educational Science, 16(4). https://doi.org/10.38089/kuteks.2023.111
Tripathi, A., Agrawal, S., & Gupta, R. (2021). Comparison of GIS-based AHP and fuzzy AHP methods for hospital site selection: A case study for Prayagraj City, India. GeoJournal, 87, 3507–3528. https://doi.org/10.1007/s10708-021-10445-y
Turner-Skoff, J. B., & Cavender, N. (2019). The benefits of trees for livable and sustainable communities. Plants, People, Planet, 1(4), 323–335. https://doi.org/10.1002/ppp3.39
Wan Nordin, W. N. H., Othman, S. A., Ramli, M., Abdul Rashid, S. A., & Sukri, N. N. N. (2023). Utilizing the fuzzy analytical hierarchy process (FAHP) approach to identify the best online food delivery services. Journal of Mathematics and Computing Science, 9(1), 1–12.
