Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

Abstract

The optimal management of personal resources impacts everyone’s quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students’ university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method.

Enhancing Data Management Strategies with a Hybrid Layering Framework in Assessing Data Validation and High Availability Sustainability

“…Data are essential elements for the operation of many different computer systems, ranging from smartphones and Internet of Things (IoT) devices to powerful server infrastructures, as well as significant operations for modern business environments, including business analysis, operational decisions [1], driving innovation [2,3], and enabling competitive differentiation. Data, in their volume and variety, affect every aspect of operations, making them not only a strategic asset [4] but also something that must be managed systematically and efficiently.…”