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

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