Impelementasi Data Mining terhadap Evaluasi Kinerja Guru dalam Mengajar Menggunakan Metode Naive Bayes Classifier

Abstract

Teachers are an important resource in supporting the teaching and learning process. The quality of teachers needs attention because it determines the quality of the teaching and learning process. This research aims to create a system that is able to classify performance as Very Good, Good, and Fair as seen from Pedagogical Competency, Personality Competency, Social Competency, Professional Competency using Naive Bayes Classifier calculations. Implementation of the Naive Bayes Classifier classification using numerical calculations. Based on a dataset divided into 80 training data and 20 testing data, the final test calculation achieved an accuracy level of 85% with precision results of 60% then recall of 57.14%. After carrying out calculations and obtaining test results, they will be distributed into the system using PHP and MySQL which are designed to carry out teacher performance assessment classifications. The prediction results obtained from the system are consistent with the results of manual calculations. Based on the research conducted, the system developed can be implemented in a way that makes it easier to evaluate teaching effectiveness.