Moodle Web-Based Learning Constraints toward Student Learning Interest Using C4.5 Algorithm during Covid-19 Pandemic


N. PRIYA DHARSHINNI(1*), Aisyah Hikmasari Sitepu(2), Rezza Youan Syuhada(3), Damanik Barasa(4), Andy Christanto Wijaya(5),


(1) Universitas Prima Indonesia
(2) Universitas Prima Indonesia
(3) Universitas Prima Indonesia
(4) Universitas Prima Indonesia
(5) Universitas Prima Indonesia
(*) Corresponding Author

Abstract


The Learning System during the Covid-19 pandemic shifted from offline learning to online learning which made many campuses use various E-Learning platforms. However, most campuses use Moodle Web-Based Learning because it provides many features that can support lecturers and students in the online learning process and can be accessed via a laptop or smartphone. The problem is, some students experience constraints in following this learning model that affects the ups and downs of student interest in learning, so it is necessary to find the obstacle factors that hinder students during Moodle Web-Based Learning. The C4.5 algorithm generates a decision tree that can be used to predict good results and provide accurate information. The purpose of this study was to find the relationship between the contraints experienced by students while following the Moodle Web-Based Learning model toward students' interest in learning using the C4.5 algorithm. The results showed the main contraint that affects the decrease in student learning interest is influenced by the learning features used by lecturers at a time when online learning is incomplete, network quality is not good, students consider Moodle Web-Based Learning less interesting while the increasing interest in student learning is influenced by the learning features used by lecturers at the time of online learning is very complete , good network quality, students use laptops or computers in following moodle Web-Based Learning and students find Moodle Web-Based Learning interesting.


Keywords


Moddle Web-Based Learning Constraints, Learning Interest, C4.5 Algorithm, Covid-19.

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DOI: https://doi.org/10.31289/jite.v5i1.5301

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