Analisis Sentimen Pengguna terhadap Aplikasi ChatGPT di Google Play Store: Penerapan Algoritma Support Vector Machine - Ardiansyah, Angga; Suleman, Suleman; Pratama, Eva Argarini; Fadlilah, Nuzul Imam (Universitas Multi Data Palembang, 2024)
Sentiment analysis is the process of identifying attitudes, opinions, or feelings towards data or objects. The results of sentiment analysis can be categorized into two types, namely positive and negative sentiment. This research utilizes the Google Play Store which is used by the public as an object for sentiment analysis. Data was collected. Data collection was carried out using the scraping technique, then processed in RapidMine. The process for analyzing this sentiment uses the Support Vector Machine algorithm using 300 data. Next, testing was carried out using the Confusion Matrix to evaluate the performance of the classification results. From testing, accuracy was obtained at 88.74%, precision at 96.54%, recall at 83.23%, and AUC at 98.7%. Of the total 300 review data, 144 positive review data were predicted correctly, 28 negative review data were included in the positive prediction, 6 positive data were included in the negative prediction, and 122 negative data were in accordance with the negative prediction