Analisis Sentimen terhadap Ulasan Pengguna Aplikasi Gojek dengan Menggunakan Pemrosesan Bahasa Alami - Yuliani, Silvia Putri; Muharani, Ari Ati Putri; Fatmawati, Riyana Qori; Fahmi, Faisal (Universitas Pancasakti, 2025)
Gojek, a leading proponent of on-demand services in Indonesia, has garnered a total of 142 million downloads. However, it has received the fewest reviews compared to other on-demand applications. The objective of this research is to identify sentiment in Gojek application user reviews on Google Playstore using Natural Language Processing (NLP) approaches and machine learning algorithms through the Orange platform. The reviews utilized in this study were collected in June 2025 and encompass a total of 3,615 data points, including 2,892 training data and 723 testing data. Sentiments are classified into two categories based on their ratings: positive (rating 4-5) and negative (rating 1-2). The research process is comprised of four primary stages: data collection and labeling, text pre-processing, feature transformation using TF-IDF, and testing five classification algorithms: neural network, naïve Bayes, random forest, decision tree, and k-nearest neighbors. The evaluation results indicate that the Neural Network model demonstrates optimal performance, exhibiting 93.20% accuracy, 93.00% F1-score, and 75.80% MCC. These findings suggest that the NLP approach can be utilized effectively to comprehend user perceptions of applications. It is anticipated that this research will assist Gojek developers in the monitoring and enhancement of service quality, with this enhancement being informed by user feedback.