Abstract

This study aims to analyze tweets about the imposition of Community Activity Restrictions (PPKM) level 3 to find the number of positive, negative, and neutral responses by building webbased software to conduct sentiment analysis on tweets data with the keywords “PPKM level 3". This research consists of two increments. The first increment is modeling and sentiment analysis and the second increment is making a website for visualizing the results. The results in the first increment are a model to perform sentiment analysis with an accuracy of 76.59% for training and for testing, with an accuracy of f1-score 75% with the test results on the macro average precision 82%, recall 73%, f1-score 75% with support of 20 and weighted average precision 80%, recall 75%, f1-score 75% with support of 20 and dataset analysis results with 30.82% positive sentiments, 17.80% neutral sentiments, and 51.36% negative sentiments. The result in the second increment is a website for visualization.

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