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All Journal Jurnal Riset Informatika Pengabdian Kepada Masyarakat Bidang Teknologi dan Sistem Informasi
Puji Astuti
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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BITCOIN PRICE VOLATILITY ANALYSIS: A DEEP LEARNING APPROACH TO X (FORMERLY TWITTER) SENTIMENT Puji Astuti; Rangga Sidiq Endrasmoyo; Syawalluddin; Yesi Fitria; Pungkas Budiyono
Jurnal Riset Informatika Vol. 8 No. 1 (2025): Desember 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1039.697 KB) | DOI: 10.34288/jri.v8i1.432

Abstract

This study investigates the relationship between social media sentiment and Bitcoin price volatility using advanced natural language processing techniques. We collected X data from April 10-29, 2025, analyzing cryptocurrency-related tweets alongside Bitcoin price movements obtained through the CoinGecko API. Five sentiment analysis methodologies were comparatively evaluated: VADER, TextBlob, BERTweet, RoBERTa Base, and RoBERTa Large. Bitcoin price volatility was measured using log returns to capture market fluctuations accurately. Correlation analysis revealed significant differences in methodological effectiveness. Traditional lexicon-based approaches (VADER and TextBlob) demonstrated weak correlations with volatility (r = -0.2232 and r = -0.0710 respectively). Transformer-based models showed superior performance, with RoBERTa Large achieving the strongest correlation (r = 0.4569, p = 0.0428), representing the only statistically significant relationship. The positive correlation indicates that increased social media sentiment corresponds to higher Bitcoin price volatility rather than directional price movements. These findings demonstrate that sophisticated deep learning models can effectively capture sentiment-driven market dynamics, providing valuable insights for cryptocurrency investors, trading platforms, and market analysts seeking to understand social media influence on digital asset markets.
Pemanfaatan Google Sites Sebagai Media Promosi Digital Dalam Meningkatkan Eksistensi Pencak Silat Walet Puti Nia Nuraeni; Ratih Yulia Hayuningtyas; Puji Astuti; Anggun Yuli Asih
Pengabdian kepada Masyarakat Bidang Teknologi dan Sistem Informasi (PETISI) Vol. 4 No. 1 (2026): Pengabdian Kepada Masyarakat Bidang Teknologi dan Sistem Informasi
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/petisi.v4i1.4602

Abstract

This community service activity aims to enhance the visibility and attractiveness of Pencak Silat Walet through the use of a Google Sites–based digital profile as a promotional medium. In the digital era, online platforms play an important role in introducing and preserving local culture, including traditional martial arts such as pencak silat. The main problem identified is the limited use of effective and modern promotional media, resulting in low public awareness of Pencak Silat Walet. To address this issue, a digital profile was developed using Google Sites, accompanied by training for members and administrators. The implementation method included needs analysis, content design, website development, and training sessions. The website content consists of organizational profiles, history, activities, documentation, and membership registration information. The results of this activity indicate that the digital profile serves as an effective promotional tool, improves participants’ digital literacy, and increases public interest in Pencak Silat Walet. Therefore, this initiative not only supports promotional activities but also contributes to the preservation of local culture through the use of digital technology
Co-Authors Anggun Yuli Asih Nia Nuraeni Pungkas Budiyono Rangga Sidiq Endrasmoyo Ratih Yulia Hayuningtyas Syawalluddin Yesi Fitria