Analisis Sentimen Fasilitas Belajar dan Alat Laboratorium menggunakan metode Naïve Bayes Classifier - A Ulfah Tenripada Syahar; Avin Savitri; Dewi Widyawati; Hariani Ma’Tang (Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI), 2024)
ABSTRACK This study aims to analyze student sentiment towards learning facilities and laboratory equipment using the Naïve Bayes Classifier method. The data used in this study were obtained from social media platforms, which include student comments and statements regarding the facilities and tools available at educational institutions. The collected data is then analyzed to identify the sentiments contained, namely positive, negative, and neutral. Based on the analysis results, 170 negative sentiments, 135 positive sentiments, and 147 neutral sentiments were obtained. The Naïve Bayes algorithm produces an accuracy value of 77%, precision of 75%, recall of 66%, and F1-score of 7%. These results show that Naïve Bayes can be used to classify student sentiment towards laboratory facilities and equipment, although there is still room for improvement in increasing recall and F1-score. This research provides an overview of the quality of learning facilities and laboratory equipment and identifies areas that require more attention in the improvement and maintenance of facilities in educational institutions.