ANALISIS SENTIMEN PELAKSANAAN KULIAH ONLINE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE - Marwondo; Venia Retreva Danestiara; Wiyanudin; Setiana, Elia (FKOM UNIKU, 2023)
This writing aims to assess the satisfaction of students regarding the implementation of online lectures, categorized into three classes: positive, neutral, and negative. Data collection was conducted using Twint from the social media platform Twitter, with a total of 25,000 tweets. The data processing process to determine sentiment analysis utilized the support vector machine algorithm. With this algorithm, the obtained results show an accuracy rate of 76.86% for positive sentiment. The precision is 0.49, recall is 0.53, and the F1 score is 0.51