The application of naive bayes method for final project topic selection within the project-based learning framework in the data mining course

Abstract

This study aims to explore the potential application of the Naive Bayes Method in predicting the determination of final project topics for students within the context of project-based learning (PBL) in the Data Mining course. Adopting an observational quantitative approach, the research involved 34 students from the Educational Technology Informatics Study Program at Padang State University between 2013-2015 as research subjects. The sampling technique employed was stratified random sampling, aligning with the research findings. The study's results indicate that the Naive Bayes Method is proficient in providing accurate predictions concerning the determination of final project topics, with significant accuracy, precision, and recall values. Moreover, the integration with project-based learning (PjBL) approach effectively enhances the authenticity and relevance of the learning experience for students, further substantiating the effectiveness of Project-Based Learning (PjBL).