Sentiment analysis using naive bayes for reviews of visitors to Padang City beach tourism after the COVID-19 pandemic

Abstract

The COVID-19 pandemic has an impact on the economy of Padang City. To revive the economy, especially in the tourism sector, the government is trying to improve services to visitors so that the number of tourist visits increases again. As one of the efforts is to find out the opinion of tourists on the beach tourism area visited. This research aims to assist the Padang City government in knowing the positive or negative responses of tourists through the sentiment analysis process to the beach tourism they visit so that The Government of Padang City can determine the policies to be taken in connection with the reviews given by beach tourism visitors. By using reviews on Google Maps on the attractions of Air Manis Beach, Padang Beach, Pasir Jambak Beach, Nirwana Beach, and Pasir Putih Beach, clustering is carried out with the Naive Bayes classification algorithm. Based on the results of the analysis that has been done, 2 of the 5 beaches get negative reviews, namely Pasir Jambak Beach and Pasir Putih Beach which get negative values of 0.550 and 0.650.