AI Technology Modeling for Monitoring and Evaluating Faculty Research Performance at Politeknik
DOI:
https://doi.org/10.46808/iite.v2i1.81Keywords:
Artificial Intelligence, Research Monitoring, Research Evaluation, Machine Learning, Natural Language ProcessingAbstract
In today’s tech-savvy world, artificial intelligence (AI) is shaking up how we handle various tasks, including managing research in educational institutions. This paper looks into how AI can be used to keep track of and evaluate the research work of faculty members at Politeknik Jambi. The main goal is to create and use an AI-driven system that makes monitoring and assessing research performance quicker and more accurate. This system uses machine learning to sift through research data, such as publications, patents, and conference contributions, to give a clear and objective view of research performance. We gather data from different sources, process it using Natural Language Processing (NLP) to pull out key info, and apply predictive models to evaluate performance. Our findings show that this AI system speeds up the evaluation process and boosts both transparency and accuracy. We also talk about the challenges of using AI in academic settings and offer some tips for future improvements. Our hope is that other educational institutions can use these insights to better manage and evaluate research with AI.