Sentiment Analysis User Ajaib Application Using Naïve Bayes Algorithm

Suwanda Aditya Saputra; Beni Rahmatullah; Pungkas Budiyono

doi:10.52362/jisicom.v6i2.964

Suwanda Aditya Saputra Univeristas Bina Sarana Informatika
Beni Rahmatullah Universitas Bina Sarana Informatika
Pungkas Budiyono Universitas Bina Sarana Informatika

DOI: https://doi.org/10.52362/jisicom.v6i2.964

Abstract

There are many advantages if everyone can invest in stock investments that are well known to the public. To facilitate and increase the interest of investors in storing shares in securities, a technology application is needed to assist investment transactions. Ajaib Application is one way to invest in both stocks and mutual funds. To provide information to the public, it is necessary to have a sentiment analysis on how the opinion of Ajaib application users uses the Naïve Bayes method with the results of scraping reviews on Google Play as many as 400 reviews. then the text processing stage is carried out to the classification stage, so that it gets an accuracy value of 89.00%, a recall value of 93.50%, a precision value of 86.36%, and an AUC value of 0.570 and the top 5 words include application words 186 repeated, magic words 77 repeated, good words 76, investment words 72 repeated and 72 easy words repeated. From the results, it can be said that there are more positive sentiments than negative sentiments in the Ajaib Application.

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