This thesis examines user sentiment towards Panca Budi Development University by utilizing Google reviews as the main data and using the Naïve Bayes algorithm for sentiment analysis. This research aims to understand the public's perception of the university through reviewing reviews available on the Google platform. The data used consists of user reviews collected from Google Reviews. The analysis process begins with data pre-processing, including text cleaning and tokenization, followed by the development of a Naïve Bayes model for classification of review sentiment into positive, negative, or neutral categories. The results of this analysis provide insight into the strengths and weaknesses of Panca Budi Development University from a user perspective, as well as identifying areas that require improvement. It is hoped that these findings can become a basis for the university to improve the quality of its services and reputation in the eyes of the public. This research also highlights the effectiveness of the Naïve Bayes algorithm in sentiment analysis, and contributes to further studies on sentiment analysis in the education sector
                        
                        
                        
                        
                            
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