Analisis Sentimen Aplikasi Mobile Bangking Bca Pada Ulasan Pengguna di Google Play Store Menggunakan Metode Naive Bayes
Abstract
An application is a program that is developed to meet user needs. M-banking is one application that makes it very easy for users to make transactions anytime and anywhere. The services contained in the M-banking application make users do not need to bother visiting ATMs or banks. The number of BCA Mobile application installations through Playstore reached more than 50 million users The development of technology is currently increasing rapidly, including applications in the field of banking which are now widely used for mobile transactions without the need to go to a bank or ATM Of course, this makes it very easy for users or customers to make transactions using the mobile banking application. User reviews are an important source of information for developers to find out complaints from users or customers. User comments and ratings in reviews are needed by developers to improve the quality and performance of M-Banking applications. However, this does not guarantee satisfaction for application users. To identify the sentiment of BCA Mobile application users, sentiment analysis will be carried out with the Naive Bayes algorithm. This aims to assess the accuracy of the Naive Bayes algorithm. This study aims to determine the results of sentiment through comments from application users and to determine the results of accuracy, precision and recall. Whether the results of this analysis will be greater than positive or negative values. At the same time to see how accurate it is if sentiment analysis is classified with the Naive Bayes method. The data used is obtained through web scraping from 1000 user reviews on the Google Play Store application. For after web scrapping, a preprocessing stage will be carried out, and the data is divided into 60% training data and 40% training data.
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References
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