Analisis Sentimen Komentar Netizen Di Twitter Terhadap Keputusan Mahkamah Konstitusi Pada Hasil Pemilihan Presiden 2024 Menggunakan Algoritma Naïve Bayes

This study aims to build and evaluate a sentiment classification model using the Naïve Bayes algorithm. The dataset used consists of two sentiment classes, namely positive and negative. The model training and testing process was carried out by dividing the data into training data and test data. The evaluation results on the test data showed that the model was able to classify sentiment with an accuracy of 87.5%. In addition, the model also had a precision value of 63.33%, a recall of 82.61%, and an F1-score of 71.70%. Based on these results, it can be concluded that the Naïve Bayes algorithm is quite effective in recognizing positive sentiment although there are still errors in classification. This model can be used as a baseline for the development of more complex sentiment analysis systems in the future.