Decision Support System for Determining Thesis Supervisors Using the Profile Matching Method Based on VB.Net - Wesni Muliana Tanjung; Wafiq Nurul Karim; Amanda Salsabila Damanik; Tinur Maya Sidabalok (Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara, 2026)
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