Sistem Informasi Evaluasi Perkuliahan dengan Sentimen Analisis Menggunakan Naïve Bayes dan Smoothing Laplace - Ramadhani, Nilam; Fajarianto, Novan (JSINBIS (Jurnal Sistem Informasi Bisnis), 2020)
A good lecture is certainly a goal so that students achieve maximum learning outcomes. In order for good lecture quality, lecture evaluation needs to be done,beside lecturer professional competency training. In order to improve the quality of lectures, Departement Informatics of Madura University (UNIRA) evaluates lecturers' performance in each semester. Form of evaluation is a questionnaire that filled out by students.Results of the questionnaire, then it is analyzed to find out whether the comments are positive, negative, or neutral. The method that can be used to solve the problem of sentiment classification analysis is Naïve Bayes that combined with text processing techniques.The data comments that collected are 342. After grouping the comments by subject, there were 31 comments for subject Human and Computer Interaction (HCI). In this data comments then performed data cleaning, data transformation, text processing and labeling. Then classifying comments using Naïve Bayes with Smoothing Laplace. Results of accuration obtained an accuracy to 80%. The results of  implementation Naïve Bayes algorithm with Smoothing Laplace, it can be seen the sentiment analysis of the subjects that lectures taught.