Analisis Sentimen Pinjaman Online Di Media Sosial Twitter Menggunakan Metode Naive Bayes - Muhammad Imam Ghozali; Wibowo Harry Sugiharto; Ary Fajar Iskandar (KLIK: Kajian Ilmiah Informatika dan Komputer, 2023)
Sentiment analysis is conducted to measure public opinion tendencies towards ongoing or past events. One of the cases analyzed in this study is Online Loans, commonly known as "Pinjol" in Indonesian. The research data regarding Online Loans was collected from the Twitter social media platform using the keyword "Pinjaman Online." The analysis method employed in this study is Naïve Bayes. Prior to the sentiment analysis process, text data was obtained through crawling from the Twitter API using the Rapidminer application. The data was then subjected to text pre-processing. Subsequently, the data underwent TF-IDF weighting. The results of this research demonstrate the tendencies of positive and negative sentiment conflicts within each tweet discussed by Twitter users regarding Online Loans. The conclusion drawn from the sentiment analysis using the Naïve Bayes classification algorithm with data obtained from Twitter concerning Online Loans is as follows: Out of the 2931 data used, after undergoing text pre-processing, a total of 2912 data were available. Among them, negative sentiment accounted for 68.61% with 1998 data, while positive sentiment accounted for 31.39% with 914 data. The sentiment analysis of Twitter users regarding Online Loans achieved an accuracy rate of 80%.