File Prosiding ICSINTESA

File Prosiding ICSINTESA

• By Kristiyanti, Dinar Ajeng; Aulianita, Rizki; Putri ,Dwi Andini; Utami, Lilyani Asri; Agustini, Fajar; Alfianti, Zulia Imami;
• 364

The use of public transportation facilities such
as MRT, LRT, and Transjakarta by the people of the capital
city is an alternative in reducing congestion. However, the
services provided by MRT, LRT and Transjakarta
transportation service providers vary, such as positive and
negative responses. The effectiveness of public transportation
facilities can be seen through public opinion. This study aims to
classify positive and negative tweet sentiments sourced from
Twitter data using the Support Vector Machine (SVM)
algorithm. The results of this study indicate that the Support
Vector Machine method is able to classify positive and negative
sentiment text with an accuracy result of 91.89% with 79.2%
positive sentiment and 20.8% negative sentiment.
Keywords— Public Transportation, Sentiment Analysis,
Sentiment Classification, Support Vector Machine, Twitter

• Katakunci
• URL http://
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