Super App is an app for reseller agents who sell and distribute basic necessities in tier 2, 3 cities and rural Indonesia. The Super app has been downloaded by around 50,000 users on the Play Store. Various reviews or reviews have also been given by users who have downloaded the Super application. Whether we realize it or not, customer opinions / reviews given on Google play, a little or a lot, will have an influence on potential customers. Based on the problems that occur, this research will implement a text summarization program on Super App reviews with the implementation of the MMR and TF-IDF methods, so that from the large number of existing reviews, only a few important sentences can be extracted, so that the conclusion making process will become easier. The results of the research using the MMR method produced an average precision value of 40.4% in 3 trials, and with the highest precision value of 60.4% in the experiment using the parameter value = 0.7