Sentiment Analysis Destinasi Wisata Berdasarkan Opini Masyarakat Menggunakan Naive Bayes - Rizki Alamsyah; Tb Ai Munandar; Fata Nidaul Khasanah; Siti Setiawati (Research Group of Data Engineering, Faculty of Informatics, 2022)
The topic used in this research is to discuss the problem of public opinion on social media related to tourist destinations in Bekasi Regency by implementing the Naive Bayes algorithm to conduct sentiment analysis on existing opinions. This study aims to analyze public opinion on social media towards tourist destinations in Bekasi Regency using the Naive Bayes algorithm. The data used in this study are posts or comments from the public on social media facebook as much as 1000 data. The method of data collection is done manually. The data analysis technique in this study are changing non-standard words, labelling, text preprocessing and naive bayes analysis methods. The results of this study indicate that positive opinion dominates compared to negative and neutral opinions with the results obtained at F1 positive score 83.5%, F1 negative score 68.2% and F1 neutral score 59.5% with positive recall 81%, negative 82% and neutral 55% precision positive 85%, negative 58% and neutral 64% with an accuracy rate of 76%.