ANALISIS SENTIMEN PELAKSANAAN KULIAH ONLINE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE
DOI:
https://doi.org/10.25134/ilkom.v17i2.11Keywords:
algorithm, lectures, onlineAbstract
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
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