TY - JOUR
T1 - Public Response to the Legalization of The Criminal Code Bill with Twitter Data Sentiment Analysis
AU - Irawan, Deny
AU - Sensuse, Dana Indra
AU - Putro, Prasetyo Adi Wibowo
AU - Prasetyo, Aji
N1 - Funding Information:
ACKNOWLEDGMENT Thanks to the Indonesian Ministry of Communication and Information for supporting, assisting, and funding this research. As well as support from the Faculty of Computer Science, University of Indonesia.
Funding Information:
Thanks to the Indonesian Ministry of Communication and Information for supporting, assisting, and funding this research. As well as support from the Faculty of Computer Science, University of Indonesia.
Publisher Copyright:
© 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.
PY - 2023
Y1 - 2023
N2 - The Criminal Code Bill, also known as Rancangan Kitab Undang-undang Hukum Pidana (RKUHP), passed in the House of Representatives (DPR) on December 6, 2022, is being debated because several issues need to be fixed. Therefore, research was conducted to determine the public's reaction to the ratification of the Criminal Code Bill by analyzing Twitter data. This study aims to obtain a general response to the legalized RKUHP. We use sentiment analysis, a text-processing method, to get data from the public. To do this, we used N-grams (unigrams, bigrams, and trigrams) along with three algorithms: Naïve Bayes, Classification and Regression Tree (CART), and Support Vector Machine (SVM). The result of sentiment analysis found that 51% of tweets were positive about the ratification of the RKUHP, and 49% were negative. In addition, it was also found that SVM has the best accuracy compared to other algorithms, with an accuracy value of 0.81 on the unigram combination.
AB - The Criminal Code Bill, also known as Rancangan Kitab Undang-undang Hukum Pidana (RKUHP), passed in the House of Representatives (DPR) on December 6, 2022, is being debated because several issues need to be fixed. Therefore, research was conducted to determine the public's reaction to the ratification of the Criminal Code Bill by analyzing Twitter data. This study aims to obtain a general response to the legalized RKUHP. We use sentiment analysis, a text-processing method, to get data from the public. To do this, we used N-grams (unigrams, bigrams, and trigrams) along with three algorithms: Naïve Bayes, Classification and Regression Tree (CART), and Support Vector Machine (SVM). The result of sentiment analysis found that 51% of tweets were positive about the ratification of the RKUHP, and 49% were negative. In addition, it was also found that SVM has the best accuracy compared to other algorithms, with an accuracy value of 0.81 on the unigram combination.
KW - classification and regression tree (CART)
KW - Naïve Bayes
KW - RKUHP
KW - Sentiment analysis
KW - support vector Machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=85149735501&partnerID=8YFLogxK
U2 - 10.14569/IJACSA.2023.0140236
DO - 10.14569/IJACSA.2023.0140236
M3 - Article
AN - SCOPUS:85149735501
SN - 2158-107X
VL - 14
SP - 295
EP - 303
JO - International Journal of Advanced Computer Science and Applications
JF - International Journal of Advanced Computer Science and Applications
IS - 2
ER -
