Sentimen Analisis Masyarakat Indonesia Terhadap Presiden Rusia Pada Komentar Media Berita Online
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Abstract
Russia's invasion of Ukraine was criticized by various parties, including from Indonesia. The attitude shown by the Indonesian government is not the same as the response of the Indonesian people based on various comments on online news media pages. Comments by online news readers are used as an assessment of the Russian President who is involved in the conflict between Russia and Ukraine in the form of sentiment analysis. This study succeeded in obtaining data as many as 352 comments from one of the online news media, the data had previously gone through the cleansing stage to eliminate duplication. To get basic information on comments, Text mining and Text Pre-Processing become an important part of the process. The algorithm used in this research is the Naive Bayes (NB) and Support Vector Machine (SVM) classification algorithm which is optimized using Particle Swarm Optimization (PSO). The two algorithms were tested and gave the result that PSO-based SVM got the best accuracy, which was 79.90% and AUC 0.901.
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