Open AccessSentiment Analysis on Twitter about the Use of City Public Transportation Using Support Vector Machine Method
Author(s) -
Veronikha Effendy
Publication year - 2016
Publication title -
international journal on information and communication technology
Language(s) - English
Resource type - Journals
ISSN - 2356-5462
DOI - 10.21108/ijoict.2016.21.85
Subject(s) - sentiment analysis , support vector machine , public opinion , public transport , process (computing) , transport engineering , public support , computer science , business , political science , engineering , artificial intelligence , public relations , politics , law , operating system
Traffic jams that occur in big cities in Indonesia due to the increased use of private vehicles. One solution to overcome this problem is to increase the use of public transport. But, the existing public transport is still not much in demand by the community. Some people express their opinions regarding the use of city public transportation via Twitter. The opinions can be processed as a sentiment analysis to determine the positive opinions and negative opinions. The opinion will then be analyzed to determine factors that are the main cause of the ineligibility use of public transport as well as the factors that make the public choose to use this type of transport. By upgrading of facilities and services based on the results of sentiment analysis, it is expected that people will switch to use city public transportation, which would reduce the traffic jam. This research used SVM method to process sentiment analysis. The result has shown SVM accuracy reaches 78.12%, which indicates that the results of this reserach deserve to be considered.