Optimizing the Selection of Website-Based Thesis Supervisors Using the AHP and TOPSIS Methods

Abstract

The selection of a thesis advisor is a crucial step in a student's academic process, particularly in the Faculty of Engineering, Bumigora University. The manual process creates challenges such as mismatched areas of expertise, uneven distribution of the advisory workload, and potential subjectivity in decision-making. This study aims to develop a website-based decision support system that can recommend thesis advisors objectively and efficiently. The system is designed by integrating two multi-criteria decision-making methods: the Analytical Hierarchy Process (AHP) to determine the weight of each criterion and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank alternative advisors. The criteria used include department competency, number of active advisors, educational level, and functional position. Data were obtained through interviews and literature studies, while the system was developed using the waterfall model. The test results show a Consistency Ratio value of 0.052, which is below the 0.1 limit, so the criteria weighting is considered consistent and objective. In addition, a usability evaluation using the ISO 9126 standard involving 20 respondents indicates that the system is in the very good category. These findings demonstrate that the system not only provides consistent and tailored recommendations but also expedites the supervisor selection process compared to manual methods. Thus, the system has been shown to increase objectivity and efficiency in the selection of thesis supervisors while simultaneously supporting digital transformation within the Bumigora University academic environment.