Analisis Sentimen Perkembangan Cryptocurrency di Media Sosial Twitter Menggunakan Metode Naïve Bayes

Krisna Alam, Alif Imanullah (2025) Analisis Sentimen Perkembangan Cryptocurrency di Media Sosial Twitter Menggunakan Metode Naïve Bayes. Undergraduate thesis, Politeknik Negeri Jember.

	Text (Abstract) Abstract.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (162kB)
	Text (Bab 1 Pendahuluan) Bab 1 Pendahuluan.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (195kB)
	Text (Daftar Pustaka) Daftar Pustaka.pdf - Submitted Version Available under License Creative Commons Attribution Share Alike. Download (171kB)
	Text (Laporan Lengkap) Laporan Lengkap.pdf - Submitted Version Restricted to Registered users only Download (2MB) | Request a copy

Abstract

This research conducts sentiment analysis on the topic of cryptocurrency development in Indonesia through Twitter social media by applying the Naïve Bayes method and TF-IDF weighting technique. A total of 1200 tweets were used as datasets, which were processed through scraping, pre-processing, and classification stages. Model testing was carried out with a division of training data and test data of 90:10. The evaluation results show an accuracy rate of 85.00%, with a precision value of 91% for negative sentiment and 82% for positive sentiment, respectively. Meanwhile, recall was 74% for negative sentiment and 94% for positive sentiment, and f1-score reached 81% for negative sentiment and 88% for positive sentiment. Although the overall accuracy is high, the model's performance in detecting negative sentiment is still low, so strategies are needed to deal with data imbalance.

Actions (login required)

View Item