<![CDATA[Interactive learning is one of the most popular learning methods, especially during a pandemic like today. One of the interactive learning methods that is developing very quickly is e-learning-based interactive learning. For now, the e-learning learning method is a learning method that is developing rapidly, where this method minimizes face-to-face between educators and students. In e-learning learning, students can leave feedback in the form of comments, which will later become the basis for educators to make improvements to the teaching system they are working on. Thus, this study tries to classify comments on e-learning learning, in this case e-learning. - learning English. So it is hoped that the classification of comment text documents will result, whether they are included in negative or positive opinions. The classification process is carried out using the K-Nearest Neighbor algorithm. In this sentiment analysis process, there are 4 main processes, namely Text Processing, Term Weighting (TF IDF), Cosine Similarity calculation¸and finally classification using the K-Nearest Neighbor method. From the test results, it is known that the best accuracy results of 87.71% are obtained when the value of k = 1, and 71.42% using the value of k = 2.]]>
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