Analysis of Dana Application User Sentiment Using the Naïve Bayes Method
DOI:
https://doi.org/10.46229/jifotech.v4i2.899Keywords:
Sentiment Analysis, Naïve Bayes, Dana App, ReviewsAbstract
The Dana application was one of the digital wallet examples widely employed by the public for online payments. The application provided services that facilitated users, eliminating the need to carry debit cards or cash and was perceived as safer due to password protection accessible only by the account owner. Despite its widespread use, responses varied, encompassing positive, negative, and neutral feedback. One of the platforms for reviewing the Dana application was the Market Application, where it could be downloaded. Upon downloading, users could compose reviews based on their experiences with the application. However, occasionally, reviews did not align with the given ratings. To study and analyze this phenomenon, a method was required to classify user comments into several categories: positive, negative, and neutral. This research employed the Naive Bayes method to identify positive, negative, and neutral sentiments within user comments on the Dana application in the Playstore. Testing was conducted with 1000 data points, comprising 800 for training and 200 for testing, resulting in an accuracy of 88%.
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