Sentiment Analysis of Gobis Suroboyo Bus Application Feature Using Support Vector Machinery (SVM) Algorithm
Abstract
Congestion is something that often occurs in several big cities in Indonesia. According to a report from INRIX, a company that conducts data analysis and provides traffic data, in 2021 the city of Surabaya is listed as the 41st most congested city in the world, with a total wasted time of 62 hours in one year. This is of course very detrimental from various aspects, because of this the Surabaya Transportation Agency developed an application called GOBIS Suroboyo Bus to support digitizing the use of Surobyo Bus to break up traffic jams. The purpose of this study is to analyze public sentiment that has used the features in the GOBIS Suroboyo Bus application by using the application comment column on the Google Playstore to obtain data. The method used in this study is Complement Naïve Bayes which produces an accuracy value of 76.00% and Support Vector Machines which obtains an accuracy value of 73.00%.
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