<![CDATA[Social media in this digital era, especially Twitter, has an important role in the interaction between government and society. Given the wide variety of activities within government circles, the task of monitoring and responding to messages is complex and time-consuming. Therefore, this study aims to develop an effective approach in determining the appropriate response from the government to people's tweets. This study proposes using a combination of the Rabin-Karp method to quickly determine relevant responses. The Rabin-Karp method, known for its efficiency in pattern matching, is used to match tweets to a set of tweets that have already been given a response. Furthermore, the Word2Vec technique is used to improve understanding of the meaning of the text. The use of the Rabin-Karp method with the addition of the Word2Vec method shows that the response accuracy rate is 74.55%. The results of this study also show that the lower the K-Gram value, the higher the similarity value, and vice versa. These results are expected to contribute in the context of government that is responsive to societal issues discussed on Twitter.]]>
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