Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In the rapidly evolving landscape of higher education, the need for efficient, data-driven decision-making has become increasingly important. Traditional methods of administration, which often rely on manual processes and intuition, are no longer sufficient to address the complex challenges faced by educational institutions. This paper presents a Machine Learning-Based Decision Support System (ML-DSS) designed to enhance the administrative processes in higher education. The system leverages advanced machine learning algorithms to analyze large datasets, provide actionable insights, and support strategic decision- making. The paper discusses the system's architecture, the algorithms used, and the potential impact on various administrative functions such as student recruitment, resource allocation, and academic performance monitoring. The results of a pilot study conducted at a large university are presented, demonstrating the system's effectiveness in improving administrative efficiency and outcomes.
"Machine Learning-Based Decision Support System for Higher Education Efficiency", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 8, page no.a375-a382, August-2025, Available :http://www.ijrti.org/papers/IJRTI2508047.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator