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All Journal Jurnal Riset Informatika
Alisa Fitriyani
Universitas Nasional
Computer Science & IT

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Journal : jurnal riset informatika

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SENTIMENT ANALYSIS OF REKSADANA ON BIBIT APPLICATIONS USING THE NAÏVE BAYES METHOD AND K-NEAREST NEIGHBOR (KNN) Alisa Fitriyani; Agung Triayudi
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (950.443 KB) | DOI: 10.34288/jri.v4i2.304

Abstract

The public's lack of interest in the capital market has made the top brass of capital market companies compete with each other to provide services in order 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 mutual fund investment products for investors, namely PT Bibit Reksadana Grow Together, which created a mutual fund application, namely Bibit Mutual Fund with more than one million users based on data downloaded on the play store by PT Bibit Grow Bersama which acts as a Mutual Fund Selling Agent (APERD) and sells 134 mutual fund products. So, to provide information to the public, it is necessary to have a sentiment analysis on how the opinions of users of the mutual fund seed application use the methodK-nearest neighbor (KNN) and Naïve Bayes, with the results of crawling data of 3800 tweets and scraping of 5000 reviews, then the text processing and labeling stages are carried out using the textblob library, with a high level of accuracy in the classification of tweet data and review data using the K-nearest neighbor method. Nearest Neighbor as much as 88%, 100%, and Naïve Bayes as much as 100%, 100%, it can be concluded that positive opinions from seed mutual fund users are more than negative sentiments.
Co-Authors Agung Triayudi