<![CDATA[The conflict between Russia and Ukraine remains one of the major international issues drawing global attention. It began in 2014 with the ousting of President Yanukovych, which triggered a political divide between pro-European Union and pro-Russian factions within Ukraine. Tensions escalated significantly by late 2021, culminating in Russia’s military aggression against Ukraine on February 24, 2022, under President Vladimir Putin’s directive. Twitter, as a social media platform, became a major outlet for the public to express their opinions regarding the conflict. This study aims to analyze public sentiment on Twitter concerning the Russia-Ukraine conflict. The methods used in this research are a combination of the Naïve Bayes algorithm and Lexicon Based Features. Naïve Bayes is utilized to classify sentiment data, while Lexicon Based Features assign weights to positive and negative sentiment words in textual data. The results show that this combined method is effective in categorizing public opinions based on their sentiments towards the conflict. This sentiment analysis provides a broader understanding of global perceptions and may serve as a reference for assessing public opinion in digital media contexts.]]>
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