Analisis Sentimen Terhadap Ulasan Pengguna Pada Aplikasi BCA Mobile Menggunakan Metode Naïve Bayes
- Muchammad Gamma Al Hakim Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta, Indonesia
-
Faldy Irwiensyah
*
Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
Technological developments have made the payment process easier, which has resulted in a plethora of smartphone applications. As mobile phones become more prevalent, commercial and public organizations are looking to improve the services they provide by implementing mobile-based solutions. The banking industry has seen tremendous expansion, as evidenced by the use of mobile banking solutions by companies such as BCA Bank. Especially in the midst of the pandemic, the BCA Mobile app is an important advancement in online banking that provides benefits and convenience to individuals who frequently transact online. Bank BCA can continue to offer the most useful features to customers while proactively improving services that are currently lacking. This study emphasizes the importance of improving sentiment analysis techniques to understand customer feedback more fully and provide better mobile banking services. This study uses the Naïve Bayes approach to analyze user sentiment towards the BCA Mobile application on the Google Play Store by finding and categorizing user reviews based on the sentiment they exhibit i.e. positive, negative, or neutral is the objective of this study. Through online data mining, 2000 user review data were collected on January 11, 2024, resulting in 1173 sentiments, 163 positive reviews and 1010 negative reviews in total. The Naïve Bayes algorithm produced an accuracy of 86.83%, precision of 52.78%, and recall of 46.91%.
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