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All Journal Jurnal Riset Informatika Jurnal Multidisiplin Sahombu Jurnal Ilmu Komputer (JIK)
Budiyono, Pungkas
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Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology

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SENTIMEN ANALISIS APLIKASI FERIZY MENGGUNAKAN ALGORITMA NAIVE BAYES Rahmatullah, Beni; Budiyono, Pungkas; Aditya Saputra, Suwanda
Jurnal Ilmu Komputer Vol 6 No 3 (2023): Jurnal Ilmu Komputer (JIK)
Publisher : LPPM-STMIK Pranata Indonesia

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Abstract

Transportasi merupakan kebutuhan yang paling digunakan dalam aktifitas sehari-hari dalam bekerja, dan kegiatan yang lainnya. Transportasi laut salah satunya menjadi yang diminati oleh masyarakat terlebih lagi indonesia negara kepulauan. Penggunaan aplikasi Ferizy menjadi salah satu penunjang dan mempermudah dalam membeli tiket secara online, Saran dan kritik dari pelanggan guna memperbaiki sistem dan pelayanan yang diberikan. Dalam hal ini penulis memperoleh data dari komentar di playstore dan menggunakan algoritma Naive Bayes. Hasil akurasi yang didapat membuktikan komentar negative tertinggi dengan dengan Akurasi 98 % dan AUC 0.988.
BITCOIN PRICE VOLATILITY ANALYSIS: A DEEP LEARNING APPROACH TO X (FORMERLY TWITTER) SENTIMENT Puji Astuti; Sidiq Endrasmoyo, Rangga; Syawalluddin; Fitria, Yesi; Budiyono, Pungkas
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.
Development of a Web-Based Printing Service Application Using the Waterfall Model Susila, Mochamad Nandi; Haryanto, Haryanto; Fridayanthie, Eka W; Budiyono, Pungkas
Jurnal Multidisiplin Sahombu Vol. 5 No. 08 (2025): Jurnal Multidisiplin Sahombu, December (2025)
Publisher : Sean Institute

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The rapid growth of the creative industry has increased the demand for printing services that are fast, accurate, and consistent in quality. However, many printing businesses still rely on manual operational processes, including order recording, design verification, cost estimation, and production monitoring. These limitations often result in delays, miscommunication with customers, and difficulties in tracking incoming orders. This study focuses on the development of a web-based information system designed to automate the ordering process and enhance communication between customers and printing service providers. The system was developed using the Waterfall model, which consists of requirement analysis, system design, implementation, testing, and maintenance. Data were collected through field observations and interviews with the owner of a local printing business. The results indicate that the developed system provides online ordering features, design file uploads, automatic cost estimation, job status tracking, and real-time process update notifications. The implementation of this system not only improves production efficiency but also reduces recording errors and enhances customer satisfaction. This web-based solution is expected to support the digital transformation of printing service businesses in the modern industrial era.
Co-Authors Beni Rahmatullah Eka W Fridayanthie, Eka W Fitria, Yesi Haryanto Haryanto Mochamad Nandi Susila Puji Astuti Sidiq Endrasmoyo, Rangga Suwanda Aditya Saputra Syawalluddin