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

Authors

  • Sapriani Gustina Universitas Proklamasi 45

DOI:

https://doi.org/10.31763/iota.v1i2.378

Keywords:

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

Abstract

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.

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Published

2021-05-15

Issue

Section

Artificial Intelligence