Fuzzy inference system on online learning evaluation with technology acceptance model (TAM) in lecture instrument application for lecturers

Abstract

The learning process should be in accordance with the Semester Learning Plan (RPS) that has been prepared by the lecturer at the beginning of the lecture, but during a pandemic like the current one, lecturers sometimes experience need much times to make lecture learning instruments and finally they cannot prepare it well. This research was conducted to determine the implementation of Lecture Instruments to digital challenges at the Faculty of Engineering and Computer Science UMPP with the Technology Acceptance Model (TAM). This research uses quantitative methods and data collection uses questionnaires and is continued with fuzzy-based quantitative descriptive data analysis. Fuzzy Inference System can be used as a tool to represent different knowledge about a problem, as well as to model the interactions and relationships that exist between these variables. Fuzzy Inference System with 5 criteria, namely Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Behavioral Intention to Use, and Actual Use from the results of lecture surveys on Lecture Instruments that have been prepared by lecturers. Fuzzy inference data is used to get the results of lecturer performance along with recommendations for follow-up plans from the results obtained with the Technology Acceptance Model (TAM). In the fuzzy calculation, it is found that the high membership value is 0.715; 0.79; 0.8075; 0.7325; 0.425. So the minimum value is 0.715 and it can be concluded that the Semester Learning Plan application can be considered.