Open AccessThe Selection of Learning Platforms to Support Learning Using Fuzzy Multiple Attribute Decision Making
Author(s) -
Vensy Vydia,
Susanto Susanto,
Sri Handayani,
Maulana Bahrul Alam
Publication year - 2022
Publication title -
international journal of quantitative research and modeling
Language(s) - English
Resource type - Journals
eISSN - 2722-5046
pISSN - 2721-477X
DOI - 10.46336/ijqrm.v3i1.257
Subject(s) - computer science , active learning (machine learning) , the internet , process (computing) , machine learning , synchronous learning , weighting , artificial intelligence , quality (philosophy) , cooperative learning , teaching method , world wide web , mathematics , medicine , philosophy , epistemology , radiology , operating system , mathematics education
The utilization of information technology in learning has functioned as a tool in the teaching and learning process during the Covid-19 pandemic. The need for the availability of a learning platform using LMS (Learning Management System) or free e-learning that is easily obtained from the public network (internet) makes the utilization of the learning platform indispensable for the teaching and learning process. Learning platforms available on the internet can also be used independently by students. However, not all existing learning platforms can be used as the appropriate means to improve the quality of education. The educator policies are needed to utilize the existing learning platforms so that learning objectives can be achieved. This study will analyze how to choose the right learning platform for an educational institution using SAW (Simple Additive Weighting)-based Fuzzy Multiple Attribute Decision Making (FMADM) method. FMADM is a method used to find the optimal alternative from a number of alternatives with certain criteria. The purpose of this study is to assist educators in deciding the most appropriate learning platform that can be used to support the teaching and learning process during the Covid 19 pandemic.