Decision Support System for Selecting Online Teaching Methods Using the Fuzzy MCDM Algorithm

The global pandemic that has hit the world recently has forced educational institutions to adopt online teaching methods. However, choosing an effective online teaching method is a major challenge. This research develops a Decision Support System (DSS) that uses the Fuzzy Multi-Criteria Decision Making (FMCDM) Algorithm to select the best online teaching method. This system is designed to assist decision making in educational institutions by considering various criteria such as learning effectiveness, technology affordability, ease of use, and user satisfaction. This research uses data collection methods that involve surveys from lecturers and students to obtain their preferences and experiences with various online teaching platforms. The data collected is then processed using the FMCDM model to evaluate and rank teaching methods based on predetermined criteria. Fuzzy systems are used to overcome uncertainty and subjectivity in criteria assessment. The results of this research show that the system developed is able to effectively assess and rank various online teaching methods. From the analysis carried out, interactive teaching methods using videos and real-time quizzes received the highest ranking based on predetermined criteria. This suggests that the combination of engaging visual content and high interactivity is highly valued in online teaching contexts