OKTAL : Jurnal Ilmu Komputer dan Sains
Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains

ANALISIS SENTIMEN TERHADAP RUU KUHP PASAL 353 AYAT 1 DARI TWITTER DENGAN METODE NAÏVE BAYES CLASSIFIER

Basyarulhaq Fanani (Unknown)
Agus Heri Yunial (Unknown)



Article Info

Publish Date
05 Jan 2024

Abstract

This thesis aims to analyze sentiment towards the Criminal Code Bill Article 353 Paragraph 1 from data taken from Twitter using the Naive Bayes Classifier method. This research was conducted to find out the public's view of the controversial article. The data taken is in the form of tweets containing keywords related to the Criminal Code Bill for a certain period. The Naive Bayes Classifier method is used to classify tweets into positive or negative categories based on gender, age, and level of education as well as the impact of public sentiment on this article on the sustainability of democracy in Indonesia. The data used in this study is data from the online media Twitter. This study uses a quantitative method with a descriptive approach. The results of the sentiment analysis are expected to provide an overview of the public's perception of the article.

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Journal Info

Abbrev

oktal

Publisher

Subject

Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

Description

1. Komputasi Lunak, 2. Sistem Cerdas Terdistribusi, Manajemen Basis Data, dan Pengambilan Informasi, 3. Komputasi evolusioner dan komputasi DNA/seluler/molekuler, 4. Deteksi kesalahan, 5. Sistem Energi Hijau dan Terbarukan, 6. Antarmuka Manusia, 7. Interaksi Manusia-Komputer, 8. Hibrida dan ...