<![CDATA[One of the important steps in the improvement of the education system in Indonesia is the introduction and implementation of the Merdeka Curriculum which is designed to provide greater flexibility in curriculum development at the Primary and Secondary levels leading to increased student participation in learning according to their respective interests and talents. The method used in this research is text-based sentiment analysis using the Naïve Bayes algorithm to classify positive and negative sentiments. The data used are student responses to the implementation of the Merdeka Curriculum collected through a survey with 507 data collected and analyzed using the Naïve Bayes algorithm with an accuracy rate of 82%. The results of this sentiment analysis will provide recommendations that may be implemented as a follow-up regarding the sentiment analysis of the Merdeka Curriculum.]]>
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