Modelling Usage M-Learning using Mamdani Fuzzy Logic System in along Covid-19 Pandemic at ITS - Indonesia

Fuzzy logic system (FLS) of Mamdani is a method that has the ability to reason similar to human abilities. In this paper is conduct the modelling of usage m-learning. The model systems is able to measure qualitative categories in modeling the usage of mobile-learning during the Covid-19 pandemic. Fu...

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Bibliographic Details
Published in:	2021 13th International Conference on Information & Communication Technology and System (ICTS) pp. 190 - 194
Main Authors:	Arifin, Syamsul, Aisjah, Aulia Siti, Suharsono, Ferina Putri
Format:	Conference Proceeding
Language:	English
Published:	IEEE 20-10-2021
Subjects:	Analytical models COVID-19 Fuzzy logic Fuzzy Mamdani Instruments intention behavior Numerical analysis Pandemics peer student readiness SEM Systems modeling teacher readiness Usage m-learning
Online Access:	Get full text
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Summary:	Fuzzy logic system (FLS) of Mamdani is a method that has the ability to reason similar to human abilities. In this paper is conduct the modelling of usage m-learning. The model systems is able to measure qualitative categories in modeling the usage of mobile-learning during the Covid-19 pandemic. Fuzzy logic system model for "perceptions of student behavior in usage m-learning", with 4 variables, i.e. (i) Teacher Readiness-TR, (ii) Student Readiness - SR, (iii) Subjective Norms - NS, and (iv) Intention Behavioral - IB. The four variables are indicators that stated in the question instrument. The fourth variables is input modelling system. Each instrument with a grading answered, i.e.: strongly disagree (SA), disagree (D), neutral (N), agree (A), and strongly agree (SA). The model is structured into two subsystems. Output of sub-system 1 is TR, SR, NS and IB variables, and output of sub-system 2 is "Behavior of Usage m-learning (UB)". Model system is design in 3 scenarios, to choose the best one. The difference of each scenarios is in the interval variations and number of membership functions of fuzzy logic system. The SLF model was tested on 546 respondents. The fuzzy model in 3 scenarios shows the Mean of Average Percentage error (MAPE) value in the range of 5 - 50%, while the test results using SEM (Structural Equation Modelling) software show the MAPE value is 12%.
DOI:	10.1109/ICTS52701.2021.9609079