A Student Grouping Based on Final Exam Values of the Courses with the K-Means Classification Method Using KNIME

A Student Grouping Based on Final Exam Values of the Courses with the K-Means Classification Method Using KNIME

Kmeans, Classification, Machine Learning, Unsupervised Learning, Students Classification, Online Learning.

In learning, each student must have a different way of learning and learning patterns which will have an impact on the results of their learning evaluation at the end of each semester. Assessing a student who excels in learning is one of them by looking at the score of the final exam results that maybe the student can easily get good grades because they do have expertise in that field or get good grades because they are diligent in studying. The scores of students' final semester exams in several courses will be summarized here in order to be used as a basis for classifying students into several groups, namely smart, average, and less good students.

Gustina, Sapriani

Internet of Things and Artificial Intelligence Journal; Vol. 1 No. 2 (2021): Volume 1, Issue 2, 2021 [May]; 114-119

2774-4353

Association for Scientific Computing, Electronics, and Engineering (ASCEE)

2021-05-15

Copyright (c) 2021 Internet of Things and Artificial Intelligence Journal

https://ascee.org/

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eng

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