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Siti Rahmawati
Universitas Jenderal Achmad Yani Yogyakarta
Computer Science & IT

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Public Sentiments Analysis about Indonesian Social Insurance Administration Organization on Twitter Siti Rahmawati; Muhammad Habibi
IJID (International Journal on Informatics for Development) Vol. 9 No. 2 (2020): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2020.09205

Abstract

Insurance Administration Organization, which can be used by all people. However, this organization has received various criticisms from the public through social media, namely Twitter. This study aims to analyze public sentiment about the Indonesian Social Insurance Administration Organization on Twitter. The method used in this research is the Naive Bayes Classifier (NBC) method and uses the Support Vector Machine (SVM) method as a comparison. The amount of data used was 12,990 tweets with a data collection period from September 14, 2019 - February 18, 2020. The study compared the two classifier models built, namely the classifier model with two sentiment classes and four sentiment classes. The accuracy results show that the SVM method has a better accuracy value than the NBC method. SVM has an accuracy value of 63.60% and 82.77% for the two sentiment classes in the four sentiment classifier model. The tweet classification results show that the public's conversation about the Indonesian Social Insurance Administration Organization on Twitter has a negative polarity value tendency.
Co-Authors Muhammad Habibi