Open AccessSupport Vector Machine: Analisis Sentimen Aplikasi Saham di Google Play Store
Author(s) -
Sri Lestari,
Sudin Saepudin
Publication year - 2021
Publication title -
jurnal sistem informasi
Language(s) - English
Resource type - Journals
eISSN - 2623-1662
pISSN - 2460-092X
DOI - 10.19109/jusifo.v7i2.9825
Subject(s) - support vector machine , sentiment analysis , computer science , investment value , stock (firearms) , value (mathematics) , investment (military) , artificial intelligence , data mining , operations research , machine learning , finance , business , mathematics , engineering , political science , law , mechanical engineering , cash , politics
The best application predicate has been awarded to the application that has the highest downloads and high star rating on Google Play Store. In rating an application, user comments need to be considered because many stock investment apps have almost the same downloads and star ratings, so the title of best app is a problem. Based on this condition, this research aims to analyze user feedback of stock investment applications as a variable to determine which stock investment application is the best on the Google Play Store. This study using the Support Vector Machine (SVM) classification method with the support of Rapid Miner to carry out the calculation process. From this research, it produces positive sentiment values for each application, namely HSB Investment about 1,134 positive sentiments with an accuracy value of 88.70%, Ajaib about 936 positive sentiments with an accuracy value of 61.89%, Pluang about 703 positive sentiments with an accuracy value of 68.25%, Bibit about 322 positive sentiments with an accuracy value of 64.89%, and Stockbit about 124 positive sentiments with an accuracy value of 66.95%. So it can be concluded that the HSB 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.