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

Basyarulhaq Fanani; Agus Heri Yunial

Authors

Basyarulhaq Fanani Universitas Pamulang
Agus Heri Yunial Universitas Pamulang

Keywords:

Naive Bayes Classifier, the passage of the Criminal Code Bill and examine, Sentiment analyst

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.

References

Ali Firdaus, W. I. (2021). Text Mining Dan Pola Algoritma Dalam Penyelesaian Masalah Informasi . Jurnal JUPITER, 13.

Fauzan, I. (2020). ARTIFICIAL INTELLIGENCE (AI) PADA PROSES PENGAWASAN DAN PENGENDALIAN KEPEGAWAIAN – SEBUAH EKSPLORASI KONSEP SETELAH MASA PANDEMI BERAKHIR. Jurnal BKN, 13.

Hakam Febtadianrano Putro, R. T. (2020). Penerapan Metode Naive Bayes Untuk Klasifikasi Pelanggan. Jurnal TIKomSIN, 6.

Humas dan Protokol BPHN. (2022, Desember). RUU KUHP Disahkan menjadi Undang-undang.

Rita Apriani, D. G. (2019). Analisis Sentimen Dengan Naive Bayes Terhadap Komentar Tokopedia. Jurnal Rekayasa Teknologi Nusa Putra , 9.

Syarli, A. A. (2016). Metode Naive Bayes Untuk Prediksi Kelulusan (Studi Kasus: Data Mahasiswa Baru Perguruan Tinggi). Jurnal Ilmiah Ilmu Komputer, 5.