TY - GEN
T1 - Twitter Sentiment Analysis
T2 - 2020 International Conference on Data Science and Its Applications, ICoDSA 2020
AU - Khurniawan, Filip Stephanus
AU - Ruldeviyani, Yova
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/8
Y1 - 2020/8
N2 - Pros and cons of the Revision of the Indonesia's Corruption Eradication Commission (Komisi Pemberantasan Korupsi or KPK) Law 2019 encourage a wave of demonstrations throughout September 2019. In addition, some Indonesian people also expressed their opinions regarding the Revision of KPK Law 2019 through social media Twitter. This research was conducted to analyze public opinion sentiments towards the Revision of KPK Law 2019 and is expected to be an input for the government to obtain public views, as well as a reference in the decision-making process as needed. Sentiment analysis is performed using Support Vector Machine (SVM), Decision Tree, and Naive Bayes algorithm. The result shows the SVM algorithm has the highest performance and accuracy at 81.70%, followed by Naive Bayes at 80.90%, and the Decision Tree at 74.55%. Based on the results of testing in this study, it was found that more than 75% of Indonesian people who voiced their opinions through Twitter had negative sentiments towards the Revision of KPK Law 2019. The negative sentiments are caused by people who consider this regulation to be ratified in a hurry, while people who have positive sentiments assume that the Revision of KPK Law 2019 can encourage the performance of the KPK to be more objective.
AB - Pros and cons of the Revision of the Indonesia's Corruption Eradication Commission (Komisi Pemberantasan Korupsi or KPK) Law 2019 encourage a wave of demonstrations throughout September 2019. In addition, some Indonesian people also expressed their opinions regarding the Revision of KPK Law 2019 through social media Twitter. This research was conducted to analyze public opinion sentiments towards the Revision of KPK Law 2019 and is expected to be an input for the government to obtain public views, as well as a reference in the decision-making process as needed. Sentiment analysis is performed using Support Vector Machine (SVM), Decision Tree, and Naive Bayes algorithm. The result shows the SVM algorithm has the highest performance and accuracy at 81.70%, followed by Naive Bayes at 80.90%, and the Decision Tree at 74.55%. Based on the results of testing in this study, it was found that more than 75% of Indonesian people who voiced their opinions through Twitter had negative sentiments towards the Revision of KPK Law 2019. The negative sentiments are caused by people who consider this regulation to be ratified in a hurry, while people who have positive sentiments assume that the Revision of KPK Law 2019 can encourage the performance of the KPK to be more objective.
KW - decision tree
KW - naive bayes
KW - nvitter
KW - revision of KPK law 2019
KW - sentiment analysis
KW - SVM
UR - http://www.scopus.com/inward/record.url?scp=85094584996&partnerID=8YFLogxK
U2 - 10.1109/ICoDSA50139.2020.9212851
DO - 10.1109/ICoDSA50139.2020.9212851
M3 - Conference contribution
AN - SCOPUS:85094584996
T3 - 2020 International Conference on Data Science and Its Applications, ICoDSA 2020
BT - 2020 International Conference on Data Science and Its Applications, ICoDSA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 August 2020 through 6 August 2020
ER -
