SENTIMENT ANALYSIS OF REKSADANA ON BIBIT APPLICATIONS USING THE NAÏVE BAYES METHOD AND K-NEAREST NEIGHBOR (KNN) - Alisa Fitriyani; Agung Triayudi (Jurnal Riset Informatika, 2022)
The lack of public interest in the capital market has made the top brass of capital market companies compete with each other to provide services to provide convenience for customers in the various services available and provide convenience in accessing financial information. The emergence of several startup companies that provide reksadana investment products for investors, namely PT Bibit Reksadana Grows Together, which created a reksadana application, namely Bibit Reksadana with more than one million users based on data downloaded on the play store by PT Bibit Grow Bersama which acts as a Reksadana Selling Agent (APERD) and sells 134 reksadana products. So to provide information to the public, it is necessary to have a sentiment analysis on how the opinions of users of the reksadana bibit application use the K-nearest neighbor (KNN) and Naïve Bayes methods, with the results of scraping youtube as much as 33,292 and scraping reviews as much as 30,708 reviews, then the text processing stage is carried out, and labeling using the text blob library, with an accuracy rate of 99%, 99%, 99% accuracy on youtube data classification and review data with the K-Nearest Neighbor method, 99%, and 99%, 98% Naïve Bayes, it can be concluded that neutral sentiment is more than positive sentiment. , and more positive sentiment than negative sentiment.