Analisis Sentimen Kepuasan Pengguna Media Sosial Dengan Menggunakan Data Mining Dan Matlab - Silalahi, Naomi Cristin Br; Ompusunggu, Elvis Sastra (Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia, 2024)
In today's digital era, social media has become an integral part of many people's daily lives, with platforms such as Twitter, Facebook, Instagram, and TikTok being used to share opinions, experiences, and satisfaction or dissatisfaction with various products and services. This research aims to analyze social media user satisfaction sentiment using data mining techniques and Matlab. With data collected from several social media platforms, this research identifies and categorizes user sentiment as positive, negative, or neutral. The methods used include data collection, pre-processing, feature extraction, model building, and model evaluation. The results show that data mining techniques and Matlab effectively classify user sentiment, providing valuable insights for companies to improve their quality and performance based on social media user feedback.