The remaining food waste in Indonesia reaches around 46.35 million tons, with economic losses reaching 23 million to 48 million tons per year. This condition has led to various campaigns to reduce food waste from people concerned about the problem of food waste. However, the increase in food waste campaigns has yet to be accompanied by a decrease in the volume of food waste in Indonesia. This research aims to determine public sentiment toward food waste campaigns on Instagram social media and determine the accuracy of the methods used in data classification. The method used is the Naïve Bayes Classifier method. The results obtained were from a total of 118 data regarding the food waste campaign; 79% data showed that the public had a positive sentiment, and 21% other data had a negative sentiment. The accuracy results of using sentiment analysis were 78.94%; this shows that the performance of the Naïve Bayes method in classifying data is quite good.
