A Student Grouping Based on Final Exam Values of the Courses with the K-Means Classification Method Using KNIME
Dublin Core
Title
A Student Grouping Based on Final Exam Values of the Courses with the K-Means Classification Method Using KNIME
Subject
Kmeans, Classification, Machine Learning, Unsupervised Learning, Students Classification, Online Learning.
Description
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.
Creator
Gustina, Sapriani
Source
Internet of Things and Artificial Intelligence Journal; Vol. 1 No. 2 (2021): Volume 1, Issue 2, 2021 [May]; 114-119
2774-4353
Publisher
Association for Scientific Computing, Electronics, and Engineering (ASCEE)
Date
2021-05-15
Rights
Copyright (c) 2021 Internet of Things and Artificial Intelligence Journal
https://ascee.org/
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Identifier
Citation
Sapriani Gustina, A Student Grouping Based on Final Exam Values of the Courses with the K-Means Classification Method Using KNIME, Association for Scientific Computing, Electronics, and Engineering (ASCEE), 2021, accessed November 5, 2024, https://igi.indrastra.com/items/show/776