Sentiment Analysis of the Increase in Fuel Prices Using Random Forest Classifier Method
DOI:
https://doi.org/10.12928/biste.v5i1.7414Keywords:
BBM, Random Forest, Preprocessing, Streamlit, YouTubeAbstract
This research focuses on examining how the economy in Indonesia is affected by the increasing fuel prices, with a particular emphasis on the impact on the lower and middle-income populations. The announcement made by President Jokowi and his ministers about the fuel price hikes has spurred public reactions on social media platforms. The rise in fuel costs has a notable impact on people's livelihoods, especially concerning the surge in prices of essential goods. Sentiment analysis measures public opinion about the increase in fuel prices. The data taken from social media needs to be more balanced. The data is labeled with two identifications, “negative”, “positive” and “neutral”. The method used in sentiment analysis is the random forest method. This research contributes to determining the number of trees used in the model formation with public opinion data. The F1-score measurement result on the model is achieved at a value of 60%.
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