Track: Undergraduate Student Paper Competition

Abstract

Online investment is an investment activity when viewed from the age range, these investors are dominated by the millennial generation. There are many examples of mutual fund online investment applications that have been widely downloaded by the public, for example, Ajaib. Sentiment Analysis is a technique for extracting text data to obtain information about positive, or negative sentiment. This research aims to analyze sentiment on user reviews of online investment applications, namely Ajaib by utilizing review analysis on the Google Play Store. Ajaib is a mobile application-based online stock and mutual fund investment platform that was simultaneously released in 2019, where its users are millennials.  The many differences in online investment applications make Ajaib one of the superior applications in investing. This study aims to determine whether or not there are differences in features in terms of applications and services, prices, and promotions on interest in using the Ajaib application. The K-Nearest Neighbor method can help overcome the classification of opinions that are positive, or negative. After testing with K of 12, the highest accuracy results were obtained when K = 11 with an accuracy value of 85.0% with a precision of 90.2%, recall 87.5%, f1 value 88.8% with a tendency to also obtain reviews of the Ajaib mutual fund application tend to be positive.