Analisis Sentimen Masyarakat Terhadap Kasus Pembobolan Data Nasabah Bank BSI Pada Twitter Menggunakan Metode Random Forest Dan Naïve Bayes - Mualfah, Desti; Prihatin, Ananda; Firdaus, Rahmad; Sunanto (JURNAL FASILKOM, 2023)
Indonesia has recently been enlivened by the data breach case that hit Bank Syariah Indonesia (BSI) in May 2023, this has invited many responses from the public with various kinds of responses, especially on Twitter social media. Some people support BSI bank so they can restore the system they have but many criticize and blaspheme bank BSI for not being able to quickly fix its system which hackers compromised. The purpose of this study is to conduct a sentiment analysis to find out the response of the Indonesian people regarding cases of data breaches by bank BSI customers whether positive, negative or neutral. The methods used in this study are the naive Bayes method and the random forest method. Both of these methods have been widely used in the text data classification process and produce high accuracy. The dataset used is community responses from Twitter social media taken by crawling the data totaling 809 tweets. The results of this study are the accuracy of the Naive Bayes method of 74% and the random forest method of 70%.