<![CDATA[In the industrial era 4.0 a lot affects human activities, especially among students. Technology applied in the world of education is online learning. Online learning is a learning method implemented in communication media both asynchronously both text and video. In order for this learning to be more effective and much better in the future, they provide a place to provide input or feedback in the form of criticism and suggestions on social media such as YouTube, Twitter and Facebook. To find out whether online learning is getting more effective, a student emotional analysis is carried out on online learning. In this study, the Latent Semantic Indexing (LSI) method was used in classifying the emotional of students and added the N-Gram method in word selection. The process in this emotional analysis includes data collection, text preprocessing which is useful in producing clean data, N-gram, weighting using the term weighting method, Single Value Decomposition (SVD), Latent Semantic Indexing, Vector Support Machine (VSM) which results in a classification process. . The data used in this study are primary data sourced from social media such as Youtube, Twitter and Facebook. The best results occur when the N-Gram is a combination or combination. From the 5 Fold, it was obtained an average accuracy of 77%, precision 76%, recall 78% and f-measure 77%.]]>
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