Kresna Hafizh Muhaimin
ABSTRACT
Massive Open Online Course (MOOC) is an education service that provides an online learning system for people. MOOCs implement asynchronous learning and there is no limit to how many people join a class. Thus, it allows many people to receive the education that is needed by the people or even people who are interested in some topic that they want to learn. Online learning shows that a learning process does not require direct interaction between lecturer and student, that also brings up a problem where it is hard to determine if the lecture video is being understood by the student or not. A group of researchers collects brain signal data which generates EEG data from a few students while watching a few lecture videos from MOOC, which the EEG data can be used for further research to detect how the brain works when watching MOOC videos. This research implements Gated Recurrent Unit method to do prediction by using EEG data to detect if the brain is in a confused state or normal state which the main purpose is to know the performance of Gated Recurrent unit to predict brain state by using EEG. The process of this study consists of exploratory data analysis, preprocessing, GRU implementation process, and evaluation using the average accuracy in every fold. The testing result shows GRU gives the best result by looking at the average accuracy for every fold with 61% accuracy
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Index Terms
- Classification of Electroencephalogram Data on Massive Open Online Course Studying Process Using Gated Recurrent Unit
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