Ease Evaluation Using the Best Moodle Learning Management System with Data Mining Concepts

DOI

10.2991/assehr.k.200129.117How to use a DOI?

Keywords

learning management system Moodle, mining data, evaluation Moodle knowledge, education, learning

Abstract

Education is now integrated with technological developments, especially developments towards the era of industrial revolution 4.0, this is seen based on the many popular Learning Management Systems (LMS) including Moodle. Through this study, searching for the best LMS with the concept of data mining uses the Knowledge Discovery in Database (KDD) method which is applied to students in the Yogyakarta area as many as 246 people. Moodle devices that were made were tested and given to schools with attribute testing, used as many as 16 attributes including the appearance of Moodle which was considered interactive or not, speed of application access, features possessed by Moodle to the user’s final conclusion. Evaluation using the Receiver Operating Characteristic (ROC) curve and looking at the value graph with Area Under Cover (AUC). Data is processed with Rapidminer software with 9 KDD steps. From all data, empirical data testing will be conducted so that a model from Moodle LMS is formed. The results of the study show that the accuracy value is above 90%, indicating that the technique of applying data to software is categorized very well. So that the main focus in determining LMS is said to be the best can be validated and ascertained accurately in calculating data retrieval from teachers, students and school equipment as the object of research.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Harry Dhika
AU  - Fitriana Destiawati
AU  - Michael Sonny
AU  - Surajiyo
PY  - 2020
DA  - 2020/02/06
TI  - Ease Evaluation Using the Best Moodle Learning Management System with Data Mining Concepts
BT  - Proceedings of the 3rd International Conference on Learning Innovation and Quality Education (ICLIQE 2019)
PB  - Atlantis Press
SP  - 944
EP  - 952
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200129.117
DO  - 10.2991/assehr.k.200129.117
ID  - Dhika2020
ER  -