The sentiment analysis of Indonesia commuter line using machine learning based on twitter data

This paper presents The Sentiment Analysis of Indonesia Commuter Line (KRL) using Twitter data. Some of people are expressing their complaints about public transportation, especially the satisfaction of Commuter Line service on Twitter. We collected the data from Twitter to classify many public opin...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. Conference series 2019-04, Vol.1193 (1), p.12029
Main Authors: Pratama, M O, Satyawan, W, Jannati, R, Pamungkas, B, Raspiani, Syahputra, M E, Neforawati, I
Format: Article
Language:English
Subjects:
Classification
Customer satisfaction
Data mining
Machine learning
Naive Bayes
Public transportation
Random Forest
Sentiment analysis
Social networks
support vector machine
Support vector machines
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents The Sentiment Analysis of Indonesia Commuter Line (KRL) using Twitter data. Some of people are expressing their complaints about public transportation, especially the satisfaction of Commuter Line service on Twitter. We collected the data from Twitter to classify many public opinions into positive or negative label then Machine Learning model will be used as classification model to classify positive or negative opinion. Multinomial Naive Bayes (MNB), Random Forest (RF) and Support Vector Machine (SVM) is used as a model, then we measure all of model performances. And the result is Support Vector Machine produced has the highest accuracy of all with 85%. Net Sentiment Score (NSS) is also computed in order to determine whether KRL features meet customer's satisfaction.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1193/1/012029