Sentiment Analysis of Jakarta Bus Rapid Transportation Services using Support Vector Machine

Abstract

Jakarta Bus Rapid Transportation is state-own company which have services in public transportation. On October 2021, Jakarta Bus Rapid Transportation was recently trending on Twitter. Twitter public views might be utilized for the company as a decision support system for enhance and evaluate the services of the company. A sentiment analysis method may be used to examine public opinion especialy users of Jakarta Bus Rapid Transportation on Twitter. The goal of this research is to better understand Jakarta's public opinion trends about services. The researchers manually classified tweets from the Tweepy collection as Informasi, Apresiasi, Saran, or Komplain. Professionals will classify the sentiment as favorable, negative, or neutral. The data was then pre-processed to eliminate duplicates and extraneous information. The sentiment of fresh data will then be predicted using machine learning. The machine learning algorithms were then examined using a number of tests to discover which kernels and features provided the best accuracy. The result of this method shows of 92.00 percent of accuracy, 91.00 percent of precision, 92.00 percent of recall, and 2123 of support. The majority of Jakartans, according to the data, have an unfavorable impression of bus rapid transit. The majority of customers were disappointed with the services.