July 19, 2025

Scholarship Management Information System using Machine Learning Models

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The decision tree model achieved a remarkable accuracy of 0.987, ensuring its effectiveness within the system.
User acceptance ratings indicated an overall mean score of 4.57, classifying the system as 'Highly Acceptable'.
Application of data pre-processing techniques improved model integration within the scholarship management information system.
Adopting the ISO/IEC 25010 Software Quality Standards enabled a comprehensive assessment of the system's functional requirements.

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Implication

This analysis demonstrates user acceptance of a machine learning-based scholarship management system, indicating high functional suitability and usability.

Cite This Study

Daluyon et al. (2025) studied this question.

synapsesocial.com/papers/68af55c6ad7bf08b1eadbea2 https://doi.org/10.69478/best2025v1n2a024

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Implication

This analysis demonstrates user acceptance of a machine learning-based scholarship management system, indicating high functional suitability and usability.

Scholarship Management Information System using Machine Learning Models

Key Points

Discussion

Implication

Cite This Study

Scholarship Management Information System using Machine Learning Models

Key Points

Discussion

Implication

Cite This Study

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