<![CDATA[At present there are various kinds of beauty products. With a variety of products, the selection of beauty products in accordance with the needs must be done to get the best results. One way to choose beauty products for consumers is to look at reviews along with ratings of the products to be purchased. But with the existence of various review sources, it is not uncommon for the review not to be accompanied by a rating, making it difficult for the consumers to see whether the product to buy is a good product or not. Therefore, this research aims to categorize the review into a rating so that it is easier for consumers to determine the selected product. The system built in this research uses the Contextual Valence Shifters and Linear Regression methods and the use of n-grams includes taking the word bigram, trigram, and review sentences. In system testing, the highest results for the tolerance 0 testing model are 21,6% for bigram and trigram, the tolerance 1 test model the highest accuracy is 66,5% for bigram and for sentiment review is 62,4% for bigram. From the results of the tests, the use of n-gram especially bigram had a positive impact on the results of system accuracy.]]>
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