Sentiment Analysis of JakLingko Public Transportation Program Using Support Vector Machine Faroh Ladayya, Dania Siregar, Hilmy D. Muchtar, Wiligis E. Pranoto
Universitas Negeri Jakarta, Jakarta Timur, 13220, Indonesia
Abstract
As a metropolitan city with high mobility, public transportation plays an important role in facilitating economic, business and government activities in DKI Jakarta. DKI Jakarta provincial government launched the JakLingko program to create an integrated, convenient, efficient, and affordable public transportation system. Knowledge of public opinion can help improve the service quality of the JakLingko program. The use of social media is becoming very popular nowadays. Through social media, anyone can easily express their opinion about an issue. It is used to obtain objective and latest public opinion. Sentiment analysis is a method that can be used to analyze public opinion. Through sentiment analysis whose data was collected from Twitter, it can be seen how the public opinion toward JakLingko program. In this study, public sentiment will be classified into positive sentiment or negative sentiment. As for the classification, the Support Vector Machine (SVM) algorithm is used. The results of the classification of public sentiment about the JakLingko program using SVM show good accuracy performance. In addition, a visualization in the form of a word cloud is also displayed for each positive and negative sentiment.
Keywords: Jaklingko- Sentiment Analysis- Support Vector Machine
