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Blockchain Frontier Technology (BFRONT)
Published by Pandawan Incorporation
ISSN : 28080831     EISSN : 28080009     DOI : http//doi.org/10.34306/bfront
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Library & Information Science
Security and privacy concerning blockchain technology, Blockchain theory, applications, and evolution, Smart contracts, Optimizing blockchain performance and decentralization, Ledgers and Distributed Technologies, Advanced Numerical Algorithms, Decentralized Data Storage, Data Complexity and Workflows, Administrative aspects, Decentralized Machine Learning and AI, Blockchain Applications Databases and Data Mining.
Arjuna Subject : Umum - Umum
Articles 107 Documents
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Blockchain Integration for Secure Data Provenance and Interoperable Database Management Terra Saptina Maulani; Dwi Cahyono; Yansa Sendi Fadillah; Maulidya Reva Aprianti; John Edwards
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v6i1.1025

Abstract

The rapid advancement of digital technologies has led to a significant increase in data volume and complexity, while traditional database systems continue to face challenges in ensuring data security, integrity, transparency, and interoperability across platforms, resulting in higher risks of data tampering, limited audit trails, and the formation of data silos. This study aims to examine and develop a blockchain integration model with conventional database systems to strengthen secure data provenance and enhance interoperability among heterogeneous databases. This research proposes a hybrid architecture that combines on data recording using a permissioned blockchain with off data storage through Relational Database Management System (RDBMS) or Not Only SQL (NoSQL) databases, where blockchain functions as a trust layer that records data hashes, metadata, and immutable change histories, while system evaluation is conducted through security testing, data integrity assessment, auditability analysis, latency measurement, throughput evaluation, data consistency analysis, and cross-platform interoperability testing. The experimental results demonstrate that blockchain integration significantly improves data security and traceability by providing transparent and tamper-resistant audit trails, while enabling secure and consistent data exchange across systems through integration modules and API gateways, despite introducing additional performance overhead compared to conventional database systems. This study concludes that integrating blockchain with conventional database systems is an effective approach for ensuring secure data provenance and interoperable database management, offering a balanced trade-off between security, transparency, and system efficiency, and presenting strong potential for further development in large-scale distributed data environments.
Non Fungible Tokens (NFTs) Marketplaces and Their Economic Implications Semaria Eva Elita Girsang; Shaumiwaty; Muhammad Noval Aryansah; Mario Putra Sanjaya; Marta Rodriguez
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1060

Abstract

The development of blockchain technology has driven the emergence of Non Fungible Tokens (NFTs) as unique digital assets traded through specialized marketplaces, forming a new digital economic ecosystem. Despite the rapid growth of the NFTs market, issues such as price volatility, the dominance of speculative activities, and uncertainty regarding long-term economic value remain insufficiently understood in academic studies. This research aims to analyze the role of NFTs marketplaces in shaping the economic value of digital assets, identify the factors influencing NFTs price dynamics, and evaluate the economic implications of the NFTs market for creators, investors, and marketplace platforms. This study employs an empirical quantitative approach by utilizing NFTs transaction data obtained from the OpenSea API, NonFungible.com, and CryptoSlam. The variables analyzed include NFTs prices, trading volume, liquidity, creator reputation, rarity score, and asset category. Data analysis is conducted using statistical and econometric methods to identify price determinants and market dynamics. The results indicate that NFTs values are significantly influenced by scarcity levels, creator reputation, asset utility, and the visibility provided by marketplaces. Marketplaces play a crucial role in shaping liquidity and market expectations, but they also contribute to increased volatility and speculative tendencies. This study concludes that the NFTs market has the potential to generate real economic value, yet it continues to face risks related to speculation and instability. These findings contribute theoretically to the digital economics literature and provide practical implications for the development of a more sustainable NFTs ecosystem.
Self Supervised Transformers for High Dimensional Time Series Anomaly Detection Aswadi Jaya; Derlina; Qurotul Aini; Agung Rizky; Richard Evans
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1078

Abstract

This study addresses anomaly detection in high dimensional time series data within the context of Artificial Intelligence (AI) driven software development, where modern systems generate large temporal data streams and reliable monitoring remains difficult due to noise, complexity, and limited labeled anomalies. The objective of this research is to develop an effective and scalable anomaly detection framework based on self supervised transformer models that can learn meaningful temporal representations without heavy reliance on manual annotation. The proposed method applies self supervised pretraining through masked sequence reconstruction and contrastive temporal learning on large scale, unlabeled multivariate time series datasets, followed by transformer based attention mechanisms to capture long range dependencies and compute anomaly scores. Experiments are conducted using benchmark datasets and real world system log data implemented with Python based deep learning tools and transformer architectures to evaluate detection performance. The results indicate that the proposed approach improves detection accuracy and reduces false positive rates compared to traditional statistical techniques and supervised deep learning models, particularly in high dimensional and low label settings. In conclusion, integrating self supervised learning with transformer architectures provides a robust and generalizable solution for time series anomaly detection, contributing to software analytics and monitoring systems by lowering labeling costs and improving adaptability across application domains.
Implementation of Blockchain Technology to Enhance the Security of Online Payment Transactions Ariesya Aprillia; Denok Wahyudi Setyo Rahayu; Arista Ratih; Thomas Green
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1026

Abstract

The rapid growth of digital financial services has significantly increased the volume of online payment transactions, while simultaneously intensifying concerns related to transaction security, data integrity, privacy protection, and fraud due to the limitations of centralized payment architectures, which remain vulnerable to cyberattacks, data manipulation, and single points of failure. This study aims to analyze the role of blockchain technology in enhancing the se- curity of online payment transactions by examining its core characteristics, including decentralization, transparency, immutability, and smart contracts. This research adopts a conceptual and descriptive comparative approach by synthesizing recent peer-reviewed literature to evaluate blockchain-based payment systems in comparison with conventional centralized systems. The findings indicate that blockchain implementation improves transaction security by reducing fraud risks, eliminating single points of failure, ensuring tamperresistant records, and enhancing transparency and traceability, thereby increasing user trust. These improvements contribute to more reliable, transparent, and resilient digital payment infrastructures. Furthermore, blockchain technology supports the SDGs 8 (Decent Work and Economic Growth), SDGs 9 (Industry, Innovation, and Infrastructure), and SDGs 16 (Peace, Justice, and Strong Institutions), by promoting transparency, accountability, and long-term stability in digital financial ecosystems.
Blockchain Enabled Voting System for Improving Election Transparency and Trust Nasib Nasib; Fina Nailatul Izzah; Aldila Dinanti; Az Zahrawani Ramadhan; Ikyboy Van Versie
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1035

Abstract

Elections are a fundamental component of democratic systems, yet conventional paper based and centralized electronic voting mechanisms continue to face persistent challenges related to transparency, security, auditability, and declining public trust. To address these issues, this study aims to design and evaluate a blockchain enabled voting system that can improve election transparency and strengthen voter trust by leveraging decentralization, immutability, and crypto- graphic security. The research adopts a system design and evaluation methodology that integrates an in depth literature review, blockchain architecture modeling, smart contract development, and experimental evaluation focusing on security, transparency, and performance under simulated election conditions. The results show that the proposed system successfully ensures immutable vote recording, prevents double voting through automated smart contract enforcement, enhances end to end auditability via a transparent distributed ledger, and significantly improves resistance to vote manipulation and unauthorized access when compared to conventional and centralized electronic voting systems. Performance analysis indicates that while transaction latency increases with higher voting loads due to consensus mechanisms, the system remains stable, reliable, and operational, demonstrating feasibility for small to medium scale elections. Furthermore, the decentralized architecture reduces single points of failure and minimizes reliance on trusted third parties. Overall, this study concludes that blockchain technology provides a robust and trustworthy foundation for modern digital voting systems, while also highlighting scalability, computational overhead, and real world implementation challenges that should be addressed through optimization techniques and pilot deployments in future research.
Integration of IoT and Blockchain for Business Data Security Uki Hares Yulianti; Yul Ifda Tanjung; Untung Rahardja; Ninda Lutfiani; Adele Valerry
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1040

Abstract

The background of this study is based on the growing reliance of businesses on digital data driven by digital transformation, which demands higher standards of data security and transparency. The IoT and Blockchain are recognized as key technologies that can address these issues, yet empirical research exploring their combined roles remains limited. The objective of this research is to examine the role of the IoT in strengthening business data security, the role of Blockchain in enhancing data transparency, and the effect of integrating both technologies on business data management. This study adopts a quantitative approach, with data gathered through questionnaires distributed to business practitioners who have implemented digital technologies. The data were analyzed using descriptive statistical methods and simple inferential analysis to identify relationships among the research variables. The results show that the IoT positively influences business data security through real time monitoring, while Blockchain improves data transparency and integrity through its immutable recording mechanism. Moreover, the integration of the Internet of Things and Blockchain produces a stronger impact on data security and transparency compared to their individual use. The study concludes that the adoption and integration of the Internet of Things and Blockchain provide effective strategies for organizations to enhance business data security and transparency, while also fostering stakeholder trust and supporting business sustainability in the digital era.
Leveraging Blockchain Governance and Smart Contracts for Entrepreneurs in Social Media Kanon Mommsen Wongkar; Triananda Fajar Satriawan; Nuke Puji Lestari Santoso; Noah Rangi
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1090

Abstract

Social media entrepreneurship is shaped by centralized platforms controlling algorithms, monetization, and data, often limiting autonomy and bargaining power. Blockchain governance and smart contracts offer alternative arrangements to enhance transparency, trust, and value distribution. This study aims to examine the role of blockchain governance and smart contracts as alternative institutional mechanisms for entrepreneurs in social media ecosystems, with a focus on implementation conditions, strategic opportunities, and associated limitations. This research adopts a qualitative conceptual approach based on a systematic review of indexed academic literature published between 2022 and 2025, complemented by an analysis of documentation from blockchain based social media platforms, white papers, and relevant industry reports. The analysis maps key challenges faced by social media entrepreneurs onto blockchain governance mechanisms and smart contract functionalities. The findings indicate that blockchain governance and smart contracts can enhance entrepreneurial participation, improve transparency in revenue distribution, and strengthen the protection of digital assets. However, these benefits are context dependent and con- strained by several factors, including technical complexity, unequal token distribution, and regulatory uncertainty. Therefore, blockchain governance and smart contracts should not be viewed as universal solutions, but as strategic instruments whose effectiveness depends on inclusive governance design, sufficient technical readiness, and adaptive policy frameworks to support sustainable social media entrepreneurship. This article contributes by proposing an evaluative framework to assess the implementation of blockchain governance and smart contracts in social media entrepreneurship, emphasizing alignment be- tween technological design, governance inclusivity, and ecosystem readiness.

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