SENTIMENT ANALYSIS OF THE #INDONESIATERSERAH IN THE TIME OF COVID-19 USING THE SENTISTRENGTH METHOD
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Abstract
The use of social media during the current pandemic is the choice of the community in expressing their thoughts, one of which is Twitter. With the hashtag feature in the Twitter application, people can find out the latest trending information. With the current pandemic condition that raises many social, political, economic problems and so on, making Twitter a place for people to express their emotions. Not long ago, the hashtag #IndonesiaTerserah became a byword in the community because it described the public's disappointment with the handling of the Corona virus (COVID-19) in Indonesia. This study aims to see how the sentiments of the Indonesian people through the hashtag #IndonesiaTerserah. The sentiments were analyzed through the sent-strength algorithm, and classified into 3 classes, namely positive, neutral, and negative. This algorithm uses the lexicon as the basis for calculating the weight of the sentiment strength. The stages carried out in this study are the data crawling stage, data preprocessing and word weighting. The results of this study obtained 236 tweet data with 41.5% neutral sentiment, 32.2% negative sentiment, and 26.3% positive sentiment. This research is expected to be a benchmark for stakeholders in making a decision.
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