Sentiment Analysis to Find Out Positive or Negative Opinions on Ride Hailing Application
Ain Nadia Safira, Eli Pujastuti, Hanafi Hanafi, Bayu Setiaji, Donni Prabowo, Nuri Cahyono · 2023
Ride-hailing services, particularly in the context of the Gojek app, have become a major talking point on social media platforms, especially Twitter. This phenomenon is not surprising, given that so many people now rely heavily on on-demand ride-hailing services, both as drivers and customers. In an effort to understand the growing sentiment towards these services, a system has been proposed with a classification approach using the Support Vector Machine (SVM) method. The results of this study show that this system is able to provide a fairly accurate picture of the sentiment related to Gojek services. In a series of tests conducted, the Confusion Matrix produced an accuracy rate of 0.803. This accuracy score reflects the model's ability to correctly attribute the appropriate sentiment label for about 80.3% of the overall test data used. The system is therefore instrumental in providing valuable insights into users' perceptions and responses to on-demand ride-hailing services, which is highly relevant in the evolving online transportation industry.