KLASIFIKASI SENTIMEN KOMENTAR PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

ARDILA, CITRA SEPTIVIA and Samsuryadi, L.R Retno (2024) KLASIFIKASI SENTIMEN KOMENTAR PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

The government's policy regarding coal transportation operations received various opinions from the public through comments on Instagram. People expressed their opinions about the impact they felt. The comments given are public opinions that are pro and contra related to the impact of the policy. The community's opinion is classified using the Support Vector Machine (SVM) method with polynomial, RBF, and sigmoid kernels. The highest accuracy results in the sigmoid kernel. The sigmoid kernel accuracy ratio is higher by 9.34% with 70% training data and 30% test data from 250 data. Increasing the amount of data has the potential to improve the performance of the SVM method. Key Word : Support Vector Machine, Sentiment Classification, Publik Opinion, Instagram.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Support Vector Machine, Klasifikasi sentimen, Opini Masyarakat, Instagram.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Citra Septivia Ardila
Date Deposited:	25 Jan 2024 08:31
Last Modified:	25 Jan 2024 08:31
URI:	http://repository.unsri.ac.id/id/eprint/139836

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