<![CDATA[The AFF Cup is a football competition organized by the ASEAN Football Federation, or AFF for short. The 2020 AFF Cup was held in 2021 due to the COVID-19 pandemic. The Indonesian National Team advanced to the final round and became runner-up in the championship. With the end of the championship and the Indonesian National Team having to accept defeat in the final, the public responded through tweets on Twitter. Through these tweets, it will be known how the public evaluates the performance of the Indonesian National Team in the 2020 AFF Cup. It is vital to carry out this research to obtain information regarding society's response. The research that will be conducted is sentiment analysis. Sentiment analysis will be carried out on Rapid Miner software, with the algorithms used being Naïve Bayes and K-Nearest Neighbor. The data used to perform sentiment analysis are tweets from Twitter taken using SNScrape. This research aims to analyze public responses to the Indonesian National Team in the 2020 AFF Cup. This research will determine the percentage of positive, neutral, and negative sentiments from public responses. So that later it can be concluded how the public responds to the Indonesian National Team, whether positive, neutral, or negative. It is also to find out which algorithm has the higher accuracy. The results obtained for Naive Bayes with an accuracy of 64.74% are 71.54% positive sentiment, 15.45% neutral sentiment, and 13.01% negative sentiment. For K-Nearest Neighbor, with an accuracy of 65.64% is 80.49% positive sentiment, 15.45% neutral sentiment, and 4.06% negative sentiment. Both algorithms have the highest accuracy compared to other algorithms in Rapid Miner when the sentiment analysis is performed, with K-Nearest Neighbor having slightly higher accuracy. Most tweets about the Indonesian National Team in the 2020 AFF Cup had positive sentiments. Based on these results, it can be concluded that even though the Indonesian National Team did not win the 2020 AFF Cup, the public still responded positively.]]>
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