Metode Klasifikasi Support Vector Machine (SVM) Untuk Analisis Sentimen Aplikasi Bing: Chat with AI & GPT-4 Di Google Play Store - Muslih; Meutia Hilda, Atiqah; Muhammad Jafar Elly (PETIR, 2024)
The development of Artificial Intelligence (AI), particularly through ChatGPT technology and the emergence of Bing: Chat with AI & GPT-4, forms the foundation for this research. This study conducts sentiment analysis on users of the Bing: Chat with AI & GPT-4 application using the Support Vector Machine (SVM) classification method. A total of 10,351 reviews from the Google Play Store underwent preprocessing stages, including cleaning, case-folding, tokenizing, stop word removal, stemming, and filtering. The implementation of the TF-IDF weighting method and Support Vector Machine (SVM) classification resulted in a negative sentiment of 58.37% and a positive sentiment of 41.66%, with a testing accuracy of 89.44%. Visualization using word clouds, incorporating common words in positive and negative reviews, provides insights into user preferences and dissatisfaction, particularly regarding the speed and performance of Bing: Chat with AI & GPT-4. The study concludes that improving the application's quality is crucial for future user satisfaction, and future research recommendations include utilizing data from other platforms such as the App Store and social media for comprehensive sentiment analysis.