Affiliations: [a] Department of Management Studies, Kannur University, Thalassery Campus, Palayad, Kannur, Kerala, India
| [b] CHRIST (Deemed to be University) Hosur Rd, Bengaluru, Karnataka, India
| [c] Faculty of Business, Multimedia University, Melaka, Malaysia
| [d] Accounting, Economics and Finance Area, T A Pai Management Institute, Manipal, Karnataka, India
| [e] Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia
Correspondence:
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Corresponding author: Robert Jeyakumar Nathan, Faculty of Business, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia. E-mail: [email protected].
Abstract: BACKGROUND:The selection of students at academic institutions has been a challenging affair given multiple criteria that need to be considered by the institution. Additionally, multiple evaluators and decision makers are involved in the student selection process, rendering it inconsistent. The complexity and subjectiveness in such decisions making requires new and innovative approach in order to be more systematic and transparent. OBJECTIVE:This paper presents an innovative methodology for student selection for admission into an Institute of Higher Learning (IHL) using Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Drawing on the success of using these methods in other fields, this study applies the technique and principles on student selection process. METHOD:Fuzzy Analytical Hierarchy Process (FAHP) is used in determining the weights of the criteria by the decision makers which avoids the vagueness and inconsistencies in decision making process and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method ranks finds out the best alternative solution for student selection by calculating the relative closeness from the positive ideal solution. RESULTS AND CONCLUSION:This research finds using the hybrid method is effective in student selection for IHL and makes the process efficient and bias-free. This method can be applied to various fields and uses where multi-criteria decision making is involved.
