Analisis Sentimen Ulasan Pelanggan Pada Aplikasi Fore Coffee Menggunakan Metode Naïve Bayes - Tia Anggita Sari; Estu Sinduningrum; Firman Noor Hasan (STMIK Budi Darma, 2023)
Evolution of the coffee shop enterprise in Indonesia is progressing rapidly, because coffee consumption in Indonesia continues increasing every year. In selecting the application to be used usually consider security, convenience and many promotions. But some users are still hesitant in using an application because some of the reviews are displayed, then from that problem a research is carried out using sentiment analysis to produce a classification on customer satisfaction with fore coffee using the Naïve Bayes Algorithm. The stages of this research consist of collecting data from web scraping, data preprocessing, The utilization of TF-IDF data weighting, coupled with the successful deployment of the Naive Bayes algorithm, leads to a heightened level of precision while ensuring a straightforward and prompt workflow. Results of data processing and application of algorithms. Process results data processing carried out there are 1801 data, the highest number of sentiments is positive sentiment of 1163 and 315 negative sentiments. This shows that from 1801 data comments that users the fore coffee application likes the services provided by the fore coffee baristas, but there are also the community who don't like the waiter given by the barista. The accuracy value that has been obtained after processed using the naïve Bayes algorithm, a percentage of 74.28% is obtained which can be seen that the data can be used as a basis for fore coffee in considering decision making.