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All Journal Jurnal Simetris Jurnal Teknologi Informasi dan Ilmu Komputer Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Sains dan Teknologi Jurnal Pengabdian Informatika (JUPITA) Journal of Software Engineering and Information System (SEIS) Jurnal Riset Sistem dan Teknologi Informasi Scientific Journal of Engineering Research Scientific: Journal of Computer Science and Informatics Scientific Journal of Computer Science
Tri Stiyo Famuji
Universitas Al-Irsyad Cilacap
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Public Health Social Sciences Other

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Journal : Scientific Journal of Engineering Research

 1 
Trends and Impact of the Viola-Jones Algorithm: A Bibliometric Analysis of Face Detection Research (2001-2024) Wijaya, Setiawan Ardi; Famuji, Tri Stiyo; Mu'min, Muhammad Amirul; Safitri, Yana; Tristanti, Novi; Dahmani, Abdennasser; Driss, Zied; Sharkawy, Abdel-Nasser; Al-Sabur, Raheem
Scientific Journal of Engineering Research Vol. 1 No. 1 (2025): March
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i1.2025.8

Abstract

The Viola-Jones algorithm remains a cornerstone in computer vision, particularly for object and face detection. This bibliometric study provides a comprehensive analysis of the algorithm’s academic impact and research trends, encompassing publication patterns, citation metrics, influential authors, and co-occurrence of keywords. The findings indicate a significant rise in research outputs and citations between 2016 and 2020, reflecting the algorithm's sustained relevance and application in various domains. Network visualization maps further reveal the algorithm's integration with diverse fields, including machine learning, image processing, and neural networks, emphasizing its versatility and adaptability to emerging technological challenges. Key research contributions include advancements in hybrid approaches, combining the Viola-Jones framework with techniques such as convolutional neural networks and HOG-SVM for improved detection accuracy. However, limitations such as computational inefficiency and sensitivity to environmental factors persist, presenting opportunities for innovation. This study concludes by highlighting future research directions, such as integrating deep learning and edge computing to enhance algorithmic performance in real-time and complex scenarios. This study provides a valuable reference for researchers and practitioners aiming to extend the Viola-Jones algorithm’s capabilities and applications by consolidating existing knowledge and identifying research gaps.
A Thirdweb-Based Smart Contract Framework for Secure Sharing of Human Genetic Data on the Ethereum Blockchain Famuji, Tri Stiyo; Grancho, Bernadine; Fanani, Galih Pramuja Inggam; Talirongan, Hidear; Sumantri, Raden Bagus Bambang
Scientific Journal of Engineering Research Vol. 1 No. 3 (2025): September
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i3.2025.30

Abstract

Human genetic data, crucial for advancing personalized medicine, requires secure and privacy-preserving management solutions. Traditional approaches face challenges in scalability, security, and decentralized access control. This study proposes a blockchain-based framework leveraging Thirdweb and Ethereum smart contracts to address these issues. The framework integrates decentralized storage via IPFS for cost-efficient off-chain genetic data storage, while on-chain smart contracts manage access control, encryption, and audit trails. Utilizing Solidity for smart contract development, the system ensures role-based permissions, wallet-based authentication, and immutable transaction logging. Genetic data in FASTA format, sourced from NCBI, is encrypted and linked to IPFS hashes stored on the blockchain. The architecture supports dual interfaces—command-line for developers and a Thirdweb dashboard for end-users—enabling secure data upload, access, and monitoring. Testing demonstrated functional efficacy in data integrity, access verification, and audit capabilities. Results highlight the system’s ability to enhance privacy, eliminate intermediaries, and provide transparent data governance. The integration of Thirdweb further decentralizes operations, aligning with Web 3.0 principles. Key contributions include a scalable model for genetic data sharing, a customizable smart contract template, and a user-centric design. Future work should explore advanced encryption, real-world healthcare integration, and performance optimization under high-throughput conditions. This research bridges biotechnology and blockchain, offering a robust foundation for secure genomic data ecosystems.
Co-Authors Abdul Fadlil Adiyah Mahiruna Ahmed Jaber Abougarair Al-Sabur, Raheem Alfian Ma’arif ALYA MASITHA Bambang Sumantri, R Bagus Bella Okta Sari Miranda Dahmani, Abdennasser Dede Yusuf, Dede Dianda Rifaldi Driss, Zied Erin Eka Citra Fanani, Galih Pramuja Inggam Fanani, Galih Pramuja Inngam Fathir Fauzan Purma Ramadhan Fauzi, Yuhansyah Nur Furizal Grancho, Bernadine Hakim, Walidy Rahman Iriene Putri Mulyadi Maulana Muhammad Jogo Samudro Muhammad Amirul Mu'min Muhammad Kunta Biddinika Mulyadi, Iriene Putri Novi Tristanti Pertiwi, Yuniariana Phichitphon Chotikunnan Prastowo, Muhammad Yogie Rahmat Riansyah Ramadhan, Fauzan purma Rezki Rio Anggara Saputra, Vanji Sharkawy, Abdel-Nasser Siti Mutmainah Sunardi Sunardi Talirongan, Hidear Tristanti, Novi Utami, Tri Fitri Yana Vanji Saputra6 Veithzal Rivai Zainal Wardani, Tri Kusuma Wijaya, Setiawan Ardi Yana Safitri Yana Safitri, Yana