PREDIKSI KINERJA DARI SISWA KETIKA MENJALANI UJIAN DENGAN MENGGUNAKAN KNN, LOGISTIC REGRESSION, DAN DECISION TREE

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Published: 2022-04-20
Keywords:
K-Nearest Neighbor (KNN), Logistic Regression, Decision Tree
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Enrico Liman

Abstract

In this paper, a topic is raised that discusses the performance of students in educational institutions when taking exams. The aim of making this paper is to help design effective mechanisms to improve students' academic performance. This value consists of gender, race/ethnicity, lunch, test preparation course, math score, reading score, writing score. An algorithm is a set of instructions or steps written systematically and used to solve logical and mathematical problems/issues with the help of a computer. The algorithms used in the paper are K-Nearest Neighbors (KNN), Logistic Regression, and Decision Tree. Evaluation capital in this paper uses Classification Report, Confusion Matrix, and Cross Validation.

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Vol. 17 No. 1 (2022): Jurnal Komputer dan Informatika

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Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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