ANALISIS SENTIMEN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN QUERY EXPANSION

MELATI, RIMA and Yusliani, Novi and Rodiah, Desty (2021) ANALISIS SENTIMEN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN QUERY EXPANSION. Undergraduate thesis, Sriwijaya University.

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Abstract

Sentiment analysis is used to determine someone's opinion on a topic, then classify the comments into positive or negative sentiments. Support Vector Machine (SVM) is one of thealgorithms supervised learning that predicts classes based on models or patterns from the results of theprocess training. Themethod Support Vector Machine (SVM) in general still has shortcomings when applied toshort text, one of the challenges of using short text as a case of text classification is ambiguity. One technique that can be used to help with this problem is to add afeature or query newcalled query expansion(QE). In this study, the data used are comments about LRT SUMSEL on Twitter. The test results show that the application of query expansion with the value of window size 2 has an accuracy of 76% while the value of window size 3 is 74%. Sentiment analysis using support vector machine without query expansion has an accuracy of 83%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Analisis sentiment, Support vector machine, Query expansion, Window size.
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	RIMA MELATI
Date Deposited:	20 Sep 2021 08:00
Last Modified:	20 Sep 2021 08:00
URI:	http://repository.unsri.ac.id/id/eprint/54257

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