SENTIMEN ANALISIS PUBLIK TERHADAP VIRUS COVID-19 PADA MEDIA SOSIAL TWITTER MENGGUNAKAN METODE NAÏVE BAYES

Serafim Clara, . (2021) SENTIMEN ANALISIS PUBLIK TERHADAP VIRUS COVID-19 PADA MEDIA SOSIAL TWITTER MENGGUNAKAN METODE NAÏVE BAYES. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Twitter is a social media platform where people may directly share information, express opinions and criticism. Covid-19 is an epidemic that spreads so quickly that almost the whole world feels its impact. This immediately stirred the virtual world and become the number one trending on twitter. This opinion can be analyzed with sentiment analysis which grouped them into positive sentiment and negative sentiment, then using the Naïve Bayes classification algorithm. The data was taken on December 11, 2020 in 2 regions, namely DKI Jakarta and Surabaya using the API on Twitter and also the geolocation feature with #Covid-19. The results obtained that the data from the DKI Jakarta region has the highest accuracy value in sample 2, with 78%, while the data from the Surabaya region has the highest accuracy value in sample 1 with 83%.

Item Type: Thesis (Skripsi)
Additional Information: |No. Panggil : 1710511024| |Pembimbing : Yuni Widiastiwi | |Ketua Penguji : Ermatita | |Anggota Penguji :Anita Muliawati |
Uncontrolled Keywords: twitter, naïve bayes, geolocation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Serafim Clara
Date Deposited: 21 Dec 2021 07:37
Last Modified: 21 Dec 2021 07:37
URI: http://repository.upnvj.ac.id/id/eprint/11718

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