SENTIMEN ANALISIS TERHADAP PENGGUNAAN VAKSIN SINOVAC

Trisnawati, Sherli and Unggul P, Akhmad (2021) SENTIMEN ANALISIS TERHADAP PENGGUNAAN VAKSIN SINOVAC. Masters thesis, Institut Informatika dan Bisnis Darmajaya.

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Abstract

In recent years, Twitter has become the most widely one of the most prevalent social media websites. This study analyzes public sentiment using the Sinovac Vaccine to handle the COVID-19 pandemic. This project collected English tweets from May 24, 2021 - to August 31, 2021, with the keywords Sinovac Vaccine as sentiment divided into positive, negative, and neutral forms. We used several algorithms to construct the classification model: Naive Bayes Classification (NBC), K-Nearest Neighbor (KNN), and Support Vector Machine. The training and testing data were divided into 70:30, 80:20, and 90:10. The model implementation results are evaluated using various test metrics such as confusion matrix, classification report, score model accuracy, and 10-fold cross-validation. Moreover, SVM shows the best accuracy results compared to Naive Bayes and KNN.

Item Type:	Thesis (Masters)
Subjects:	Ilmu Komputer eTheses
Divisions:	Pasca Sarjana > Magister Teknologi Informasi
Depositing User:	MTI Sherli Trisnawati
Date Deposited:	28 Jun 2022 04:31
Last Modified:	28 Jun 2022 04:31
URI:	http://repo.darmajaya.ac.id/id/eprint/7564

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