Analisis Sentimen Pengguna Terhadap Smart Ring Pada Data Twitter Menggunakan Naive Bayes

Abstract

Smart ring is a ring-shaped wearable device equipped with advanced technology to monitor user activities. Smart ring technology can be used by analyzing user sentiment, a wearable device that is increasingly popular but still faces various challenges of public acceptance. This research is to find out the opinions of users on social media, especially Twitter, and how these sentiments affect consumers' views and purchase intentions. Data was collected by crawling techniques using Google Colab and tweet-harvest tools, after which it was analyzed using the Naive Bayes algorithm to classify sentiment into positive and negative. The results showed that of the 580 tweets collected, there were 147 positive sentiments and 63 negative sentiments after duplicate removal, with an accuracy of 76.19%. This research can help smart ring manufacturers develop products that are more in line with user needs.