<![CDATA[E-Money is an innovative renewal that comes from developments in the field of technology. The impact of covid-19 is reportedly increasing. Influence of e-money has a very big impact on the digital marketing process so that a digital wallet application was created (e-wallet). On google play lots of applications e-wallet which has a high download rate. Then the reviews from users must also be calculated because there are applications that match the number of downloads and have similar ratings, which makes the application title with the best category less relevant. Existing reviews are usually used by companies to getfeedback from the community regarding the application. this comment contains hundreds to millions, it will be difficult to do it manually. One way to analyze existing comments is to use sentiment analysis. Sentiment analysis in this study uses lexicon based and k-nearest neighbors. Dictionary lexicon which is used is vader to provide labels automatically and k-nearest neighbor used for classification. The purpose and intent of the research is to find out how the community's response is classified regarding the three applications, and to find out the accuracy value of the implementation lexicon based and k-nearest neighbors on each other e-wallet. The results of the study stated that Dana got the highest accuracy of 78% on the k = 6 test, Ovo got the highest accuracy of 75.33% on the k = 9 test, and LinkAja got the highest accuracy of 73.5% on the k = 8 test. Applications that have many positive responses from users is linkaja as many as 6037 positive reviews.]]>
