Selim, Aybeyan and Ali, Ilker and Ristevski, Blagoj (2024) University Information System’s Impact on Academic Performance: A Comprehensive Logistic Regression Analysis with Principal Component Analysis and Performance Metrics. TEM JOURNAL - Technology, Education, Management, Informatics, 13 (2). pp. 1589-1598. ISSN 2217-8309
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Abstract
This paper comprehensively analyzes data mining techniques and performance metrics applied to a logistic regression model. Principal Component Analysis (PCA) was utilized to diminish the complexity of high-dimensional data, enabling clearer visualization and examination of intricate relationships among variables. The logistic regression model demonstrated commendable performance on both test and train sets, as evidenced by high values of accuracy, precision, recall, ROC AUC, and F1 Score were observed. The provided confusion matrices offered detailed insights into the model's accuracy in classifying positive and negative instances. Concerning our hypotheses, we found no significant relationship between gender and academic performance, supported by a highly significant p-value of 0.0 and a weak positive correlation coefficient of 0.0847. However, we noticed a strong positive correlation of 0.99 between gender and exam characteristics, although it has not
reached statistical significance for a p-value of 0.281.
Our research contributes valuable insights into data analysis, model evaluation, and the interplay between
variables.
Item Type: | Article |
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Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
Divisions: | Faculty of Information and Communication Technologies |
Depositing User: | Prof. d-r. Blagoj Ristevski |
Date Deposited: | 29 Apr 2025 10:56 |
Last Modified: | 29 Apr 2025 10:56 |
URI: | https://eprints.uklo.edu.mk/id/eprint/10916 |
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University Information System’s Impact on Academic Performance: A Comprehensive Logistic Regression Analysis with Principal Component Analysis and Performance Metrics. (deposited 23 Oct 2024 17:20)
- University Information System’s Impact on Academic Performance: A Comprehensive Logistic Regression Analysis with Principal Component Analysis and Performance Metrics. (deposited 29 Apr 2025 10:56) [Currently Displayed]
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