Expert System Management for Measuring the Cognitive Abilities of Sports Education Students Using the Naive Bayes Algorithm
DOI:
https://doi.org/10.71392/ejip.v5i2.147Keywords:
Pengukuran, Koginitif, Expert System, Algoritma Naive bayesAbstract
Accurate, precise, and efficient measurement of student abilities is a fundamental component of effective educational assessment. In Indonesia, cognitive evaluations in physical and sports education (PJOK) often rely on manual testing procedures that are time-consuming and prone to subjective bias. To address this challenge, this study developed an expert system using artificial intelligence to automate the measurement of students' cognitive abilities. Employing a Research and Development (R&D) approach with the ADDIE (Analysis, Design, Development, Implementation, Evaluation) framework, the system integrates a Naive Bayes supervised classification algorithm to evaluate cognitive performance. The empirical evaluation was conducted using a dataset of N = 120 student test instances. Application validity assessed by media experts reached 89.00%, placing it in the "Very Good" category. Furthermore, evaluation on a held-out test split demonstrated that the Naive Bayes model achieved a prediction accuracy of 91.67% alongside balanced precision and recall. These findings indicate that the proposed expert system provides a reliable, fast, and automated solution for cognitive diagnostic assessment in physical education.
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