Comparison of the K-Nearest Neighbor and Decision Tree algorithm to the Sentiment Analysis of Investment Applications Users in Indonesia

Abstract

Investment is a familiar thing, especially for millennials, now investment can be done easily only with a smartphone, through applications on the Google Play Store, you can invest. But these apps have the highest downloads and high ratings on the Google Play Store. Many stock investing apps have nearly the same downloads and ratings, so the title of best app is a problem. Based on this, this sentiment analysis research aims to analyze user feedback of stock investment applications as a variable to determine which stock investment application is the best. This research was conducted by using the comparison of the K-Nearest Neighbor and Decision Tree algorithms. To see the level of accuracy between the 2 algorithms. The research uses google colab tools as data retrieval tools and rapidminer as data preprocessing tools. From this research, resulting in sentiment data, the highest positive sentiment results are the Ajaib Application at 74% and Negative 26%. So it can be concluded that the Ajaib application as the best stock investment application based on user comments reviews where this application has the most positive sentiment reviews with a high accuracy value.