The Implementation of Data Mining to Determine the Level of Students' Understanding in Utilizing E-Learning Using the K-Nearest Neighbor Method
DOI:
https://doi.org/10.24014/coreit.v10i2.33728Keywords:
Course, E-Learning, Internet, K-Nearest Neighbor (KNN)Abstract
The implementation of Information Technology is increasingly developing due to the growing demand. According to data obtained from the Indonesian Internet Service Providers Association (APJII) 2022 report, the number of internet users in Indonesia is 210.02 million, an increase of 27.9 million from the previous year. The application of E-Learning in various schools, campuses, and educational courses has been carried out. The utilization of e-learning media undoubtedly facilitates educators in transferring their knowledge to students. This research evaluates the level of understanding of each student who has used E-Learning during Covid-19 as a learning medium. In obtaining this level of understanding, the K-Nearest Neighbor (K-NN) method is applied. The data analyzed are based on assignment scores, quizzes, mid-term exams, and final exams from various related courses, namely Science and Mathematics Course Group, Programming Course Group, and Basic Informatics Course Group. A total of 1,627 data points were collected from the period between 2020 and 2021 when online learning was conducted using E-Learning. The data was processed using the KNN method with an 80:20 split between training and testing data. The analyzed K values were 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21. The calculation results showed an accuracy of 75.69% at K=17 for the Basic Informatics Course Group, 77.61% at K=15 for the Science and Mathematics Course Group, and 96.20% at K=3 for the Programming Course Group.References
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