Sentiment Analysis Of Public Comments On Quick Response Code Indonesian Standard (Qris) On Twitter Social Media Using The Naïve Bayes Classifier Method - Fahri, Muhammad; Kurniawan, Rakhmat (Brahmana : Jurnal Penerapan Kecerdasan Buatan, 2024)
Nowadays, technological developments have an inevitable impact on various aspects of human life. One real example of the development of E-Wallet which is very easy to access on a smartphone. However, the large variety of e-wallets available can be confusing for users because they need to download and manage many applications on their cellphones, therefore Bank Indonesia has found a solution for faster retail transactions, namely with a QR code or known as a Quick Response Code Indonesian Standard (QRIS). The use of QRIS has become a positive trend in the business and consumer world, this is due to the benefits of more efficient non-cash transaction processing. Even though QRIS is considered easy to use and brings benefits to many parties, not everyone responds positively. Some people also have negative comments regarding the QRIS payment system. To see their various views and opinions regarding the implementation of QRIS, researchers took one of the social media platforms, namely Twitter. Therefore, a public sentiment analysis was carried out to understand how the public responded to QRIS, whether it included positive or negative sentiment? In order to achieve this goal, researchers use the Naïve Bayes Classifier method, where this method analyzes a problem with a good level of accuracy and can help in evaluating concerns that need to be corrected, in order to obtain appropriate and accurate comparison results of negative and positive sentiment in analyzing sentiment. public comments on QRIS on Twitter social media using the Naïve Bayes Classifier method