Assessing Technique For Mapping Public Response To DKI Jakarta Governor Policy In Handling COVID-19 Pandemic Using SVM BASED Sentiment Analysis
DOI:
https://doi.org/10.32528/ias.v1i1.50Keywords:
Sentiment Analysis, TF-IDF, Support Vector Machine, Youtube, NewsAbstract
Since the coronavirus outbreak or known as COVID-19 spread throughout the world, especially in Indonesia. The Governor of DKI Jakarta issued several policies to deal with the spread of COVID-19. However, this policy has become a conversation on social media such as Youtube. Through audience interaction in the comments column, giving lots of positive and negative sentiment comments, the audience response is classified using the sentiment analysis technique of comments to find out which sentiments are positive, negative, and neutral for each comment. In this study, the data were taken from news video comments. The method used is the Support Vector Machine and the selection feature uses the Term Frequency-Inverse Document Frequency (TF-IDF). The data used amounted to 945 Indonesian language comments. Accurate results obtained by using the addition of a stoplist at the preprocessing stage a.
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