ANALISIS SENTIMEN TOKOH PUBLIK TERHADAP RESPONS DEMO MENGGUNAKAN ALGORITMA DECISION TREE - renata ananda sofiarti (Universitas Ma Chung, 2026)
This study aims to analyze the responses of public figures to demonstrations in Indonesia using the decision tree algorithm as the main method of sentiment classification. This study was applied to identify patterns of public sentiment towards statements and influential factors in shaping public opinion. Data analysis using the keyword demonstration issue taken from YouTube media resulted in 999 public review datasets, then the reviews were processed using RapidMiner. The analysis process included data cleaning, tokenization, removing unnecessary words, converting words to their basic form, and labeling sentiments into negative and positive. Despite the sentiment, many public reviews were still negative towards the responses of public figures. This study also used the Decision Tree Model to classify data based on the occurrence of dominant keywords. The results of this study indicate that the decision tree algorithm achieved an accuracy of 92.88%. Decision trees are very effective and quite good when used in analyzing public perceptions of demonstration issues and government communication strategies that are more adaptive and able to reveal public sentiment. This study also contributes to the development of political sentiment analysis in Indonesia, especially understanding the dynamics of public opinion on social media. Research from social media, especially YouTube, is a relevant resource for finding reviews in real time. In addition, this research can serve as a reference for the government in developing more responsive strategies to public needs in the current digital era.