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The public's lack of interest in the capital market has made the top brass of capital market companies compete with each other to provide services in order to provide convenience for customers in the various services available and provide convenience in accessing financial information. The emergence of several startup companies that provide mutual fund investment products for investors, namely PT Bibit Reksadana Grow Together, which created a mutual fund application, namely Bibit Mutual Fund with more than one million users based on data downloaded on the play store by PT Bibit Grow Bersama which acts as a Mutual Fund Selling Agent (APERD) and sells 134 mutual fund products. So, to provide information to the public, it is necessary to have a sentiment analysis on how the opinions of users of the mutual fund seed application use the methodK-nearest neighbor (KNN) and Naïve Bayes, with the results of crawling data of 3800 tweets and scraping of 5000 reviews, then the text processing and labeling stages are carried out using the textblob library, with a high level of accuracy in the classification of tweet data and review data using the K-nearest neighbor method. Nearest Neighbor as much as 88%, 100%, and Naïve Bayes as much as 100%, 100%, it can be concluded that positive opinions from seed mutual fund users are more than negative sentiments.

Café as a place to relax or chatter where visitors can order the menu available. In general, a café often has difficulty in serving customers, especially for menu ordering facilities. This is also experienced by café 50/50 Coffee which still makes menu reservations manually. Based on these problems, a system of e-order menus of web-based mobile applications is designed. The study aims to produce a mobile web ordering system that is then analyzed with the PIECES indicator to determine the level of user satisfaction. Design of this system using the waterfall model System Development Life Cycle (SDLC) development method and then analyzed the level of user satisfaction with the PIECES method. System testing uses usability testing with the USE Questionnaire method. System implementations are created with the help of the CodeIgniter framework and use the PHP programming language. The results of the study in the form of a menu e-order system at the 50/50 Coffee café with the conclusion of the analysis that the users of the e-order system were “SATISFIED”.

Technology field following how era keep evolving. Social media already on everyone’s daily life and being a place for writing their opinion, either review or response for product and service that already being used. Twitter are one of popular social media on Indonesia, according to Statista data it reach 17.55 million users. For online business sector, knowing sentiment score are really important to stepping up their business. The use of machine learning, NLP (Natural Processing Language), and text mining for knowing the real meaning of opinion words given by customer called sentiment analysis. Two methods are using for data testing, the first is Lexicon Based and the second is Support Vector Machine (SVM). Data source that used for sentiment analyst are from keyword ‘ShopeeFood’ and ‘syopifud’. The result of analysis giving accuracy score 87%, precision score 81%, recall score 75%, and f1-score 78%.