Decision Support System for Determining Thesis Supervisors Using the Profile Matching Method Based on VB.Net

Authors

  • Wesni Muliana Tanjung STIKOM Tunas Bangsa Author
  • Wafiq Nurul Karim STIKOM Tunas Bangsa Author
  • Amanda Salsabila Damanik STIKOM Tunas Bangsa Author
  • Tinur Maya Sidabalok STIKOM Tunas Bangsa Author

DOI:

https://doi.org/10.260396/ecyyvj94

Abstract

The assignment of academic thesis supervisors plays a crucial role in ensuring the quality and timely completion of students’ final projects. In many academic institutions, this process is still carried out manually, often resulting in subjective decisions, inaccurate supervisor allocation, and imbalanced supervisory workloads. This study aims to develop a Decision Support System (DSS) for selecting thesis supervisors using the Profile Matching method, implemented in a VB.Net–based application. The Profile Matching method evaluates the compatibility between students’ profiles—such as research field, methodology, tools, and thesis topic—and lecturers’ profiles, including expertise, research interests, methodological skills, and supervisory load. The system performs calculations through several stages, including gap analysis, weight conversion, core factor and secondary factor computation, and final ranking. The developed system also includes data management features for lecturers, students, aspects, and criteria, supported by an intuitive user interface. The results indicate that the system can generate objective, measurable, and transparent supervisor recommendations, thereby improving efficiency and accuracy compared to manual selection processes.

 

Keywords: decision support system, profile matching, thesis supervisor, VB.Net, gap analysis, ranking

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References

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Published

15-07-2026

Data Availability Statement

The research data are available from the corresponding author on reasonable request.

Issue

Section

Volume 5 No 1 Tahun 2025

How to Cite

Decision Support System for Determining Thesis Supervisors Using the Profile Matching Method Based on VB.Net. (2026). Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara, 5(1), 6-12. https://doi.org/10.260396/ecyyvj94