Using a Tree-Based Algorithm to Categorize Students who have Dropped out Evidence from Universities in Vietnam

Pages 95-102

10.61552/JSI.2024.03.001

Tan Nguyen Huu, Huu Nguyen Duc

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Abstract Purpose: The purpose of this article is to identify and comprehend the mechanism of operation of the Decision Tree and Random Forest algorithms. comprehend precise implementation steps, better comprehend nature, and synthesize experience in the practice process.
Methodology: The study was conducted based on an analysis of dropout data from Trade Union University, University of Social Labour, and Phenikaa University in Vietnam.
Result: The article investigates and develops a machine learning model for classifying students as dropouts or not. Develop scales to measure the accuracy and dependability of the model.
Value: The article assesses the model's outcomes, performance, and accuracy. Give your suggestions for future development and improvement of the topic. Propose several solutions to the challenge of identifying students as dropouts, based on the real scenario employed by the algorithm during the analysis.

Keywords: Machine learning, algorithms, data mining, Tree-based, student, university, vietnam.

Recieved: 14.04.2024. Revised: 21.05.2024. Accepted: 16.07.2024.