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

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