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All Journal JISA (Jurnal Informatika dan Sains)
Syaeful Anas Aklani
Universitas Internasioanl Batam
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Mini Thesis Supervisor Recommender System Using Simple Additive Weighting Algorithm : A Case Study of Universitas Internasional Batam Syaeful Anas Aklani; Jacky Jacky
JISA(Jurnal Informatika dan Sains) Vol 5, No 2 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i2.1430

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. 
Co-Authors Jacky Jacky