<![CDATA[This research aims to analyze public sentiment towards Japanese food products in Indonesia using the Naïve Bayes Classifier method. Data was obtained from Twitter through a crawling process, resulting in 214 tweets analyzed for positive and negative sentiment. The methodology used includes data collection with Python and Google Collaboratory, as well as the application of the Naïve Bayes algorithm. The results showed that the algorithm achieved an accuracy of 77.03%, with precision for positive sentiment of 84.87% and negative sentiment of 58.06%, and recall of 83.23%. In conclusion, public sentiment towards Japanese food products in Indonesia tends to be positive, and the Naïve Bayes method proved to be reliable in this analysis.Keywords: Data Mining; Sentiment Analysis; Naïve Bayes; Japanese Food Products; Twitter AbstrakPenelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap produk makanan khas Jepang di Indonesia menggunakan metode Naïve Bayes Classifier. Data diperoleh dari Twitter melalui proses crawling, menghasilkan 214 tweet yang dianalisis untuk sentimen positif dan negatif. Metodologi yang digunakan meliputi pengumpulan data dengan Python dan Google Colaboratory, serta penerapan algoritma Naïve Bayes. Hasil penelitian menunjukkan bahwa algoritma ini mencapai akurasi sebesar 77,03%, dengan presisi untuk sentimen positif 84,87% dan negatif 58,06%, serta recall 83,23%. Kesimpulannya, sentimen masyarakat terhadap produk makanan khas Jepang di Indonesia cenderung positif, dan metode Naïve Bayes terbukti andal dalam analisis ini. ]]>
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