Analysis Sentiment Of Users Internet Service Providers In Indonesia On Social Media X Using Support Vector Machine
DOI:
https://doi.org/10.32734/jocai.v8.i2-16317Keywords:
Text Mining, Analysis Sentiment, x, Support Vector Machine, Classification TextAbstract
Various internet service providers are starting to appear in Indonesia, they are competing to provide attractive offers to attract customers. Through social media, someone can find out opinions about whether internet service providers provide services as offered. X, formerly known as Twitter, is a social media platform where people can give their opinions in the form of posts. Various opinions were expressed by the public, ranging from positive, neutral, to negative. This research aims to create a post classification model regarding users of internet service providers into three sentiment classes, namely positive, neutral and negative. The model is created through several stages, such as data retrieval, data labeling, data preprocessing, data division, term weighting, and creating a classification model using the Support Vector Machine algorithm. The results of this research show that the SVM model with a Linear kernel obtained the highest accuracy of 83% compared to the RBF kernel SVM and Polynomial kernel SVM, with an F1-score of 90% for the negative class, 66% for the neutral class, and 65% for the positive class.
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