Analisis Sentimen Terhadap Kualitas Layanan Driver Gojek Di Aplikasi Play Store Menggunakan Algoritma Naïve Bayes Dan Aplikasi Orange - Ipan Hasmadi; Rudiman Rudiman; Khoirul Huda Dwi Putra; Muhammad Farhat jundullah (STIKes Ibnu Sina Ajibarang, 2024)
The significant changes in daily life patterns, driven by technological advancements, particularly in the transportation sector, are evident through the emergence of on-demand services such as Gojek. This research aims to explore users' perspectives and opinions regarding service quality, focusing on aspects like driver behavior, responsiveness, and reliability within the Gojek platform. The Naive Bayes method is employed to analyze user sentiments toward the driver services, supported by the Orange software to comprehend the complex patterns in user reviews. Evaluation is conducted on reviews from the Play Store, resulting in an accuracy of 87.4%, F1 score of 87.6%, precision of 87.9%, and recall of 87.4%. These findings indicate the success of the model in identifying and predicting predefined variables. Through the combination of methods and software, the study concludes that sentiment analysis of Gojek's driver services can be performed efficiently and reliably, providing valuable insights for online motorcycle taxi service providers.