ANALISIS SENTIMEN CALON PRESIDEN 2024 PADA TWITTER MENGGUNAKAN SUPPORT VECTOR MACHINE

PRATAMA, M.RIZKY ZULPA and Abdiansah, Abdiansah and Alfarissi, Alfarissi (2023) ANALISIS SENTIMEN CALON PRESIDEN 2024 PADA TWITTER MENGGUNAKAN SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

Twitter has many features that can be used. One of these features is that users can share tweets or news in the form of text, photos or videos. One of the useful data on information is sentiment analysis. To find out how much the response from the public is related to the 2024 Indonesian presidential election, is it more inclined to positive sentiment, negative or neutral sentiment. One method of sentiment analysis is SVM (Support Vector Machine). The sentiment analysis on social media Twitter on presidential candidates in the 2024 election using the SVM method was tested on various percentage of data. From the test, the accuracy value is 0.66%. Several factors that influence the level of accuracy value are the percentage of training data and testing data, the data pre-processing process performed, and the percentage of positive data negative or neutral.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Twitter, SVM(Support Vector Machine), Pemilihan Umum
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing 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:	M.Rizky Zulpa Pratama
Date Deposited:	21 Aug 2023 02:25
Last Modified:	21 Aug 2023 02:25
URI:	http://repository.unsri.ac.id/id/eprint/127472

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