Mini Thesis Supervisor Recommender System Using Simple Additive Weighting Algorithm : A Case Study of Universitas Internasional Batam

Abstract

Currently, the selection if thesis supervisors in Faculty of Computer Science at Universitas Internasional Ba-tam is done based on direct consideration of the supervisor candidate’s competence, functional, and education. However, this thesis supervisor selection process is not very effective if the student doesn’t know a suitable supervisor for the topic of the thesis they have chosen. Therefore, a decision support system is required to determine the thesis supervisor so that the thesis submitted by student is match with the competence of the thesis supervisor candidate. The primary goal of this research is to create a decision support system application that can assist in determining the thesis supervisor. The Research and Development (R&D) technique was employed in this study, with the Simple Additive Weighting (SAW) decision making approach and the ADDIE model for the development process. Lecturer data was collected by distributing questionnaires. Based on the result of SAW calculations, it was found that alternative 7 (A7) and alternative 4 (A4) were the best alternative. From the result of testing on application, the application was able to provide recommendations for thesis supervisors to users based on the calculation using SAW Method. Future research may try to use or combine other decision-making methods, such as AHP or Apriori.