Analisis Sentimen Penilaian Pengguna Aplikasi ACI – Ojek Online Indonesia dengan Metode Naïve Bayes - Irawan, Michael Aria; Aryanny, Enny (Institut Teknologi Garut, 2025)
The advancement of industrial technology and current lifestyle changes are rooted in the industrial revolution. The widespread penetration of the internet and the advancement of smartphone technology have played a crucial role in the development of this business model, driving overall industry growth. With the support of GPS technology, digital payments, and mobile applications, consumers can easily order these services. The ACI – Indonesian Online Ojek Application is one example of a platform that provides this service. However, with the surge of users in this digital era, the ACI – Indonesian Online Ojek Application faces significant challenges in competing with more established competitor applications. As can be seen on the Google Play Store platform, this application still has a lower rating compared to other competitors such as Gojek, Grab, Maxim, inDrive, and Omega. The determination of the rating count on the Google Play Store has several determining factors, one of which is user evaluation in using the application. Therefore, this research aims to check whether these problems exist, by analyzing user comment data using the Naïve Bayes method, and propose improvements using the 5W+1H method. The research results show that the sentiment analysis classification analysis using the Naïve Bayes method is 0.83 or 83%, which shows that the classification results can predict 83% correctly from the overall data, and in negative sentiment, there are 4 words that appear most often, in this case, the most complained about by users are the words application, driver, restaurant, and order. Thus, it can be concluded that there is a large amount of negative sentiment from application users, and it is best for the ACI application to improve the quality of its application performance.