cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Nanda
Contact Email
b.front@pandawan.id
Phone
+6283861932019
Journal Mail Official
nanda.septiani@raharja.info
Editorial Address
Jl. Premier Park 2, RT.001/RW.011, Cikokol, Kec. Tangerang, Kota Tangerang, Banten 15117
Location
Kota tangerang,
Banten
INDONESIA
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 10 Documents
 1 
Search results for , issue "vol. 6 no. 2 (2027): blockchain frontier technology" : 10 Documents clear
Optimizing Digital Business Growth Through Effective Search Engine Optimization Practices Eko Sigit Pramudito; Marviola Hardini; Nasrul Hidayat; Ramiro Santiago Ikhsan
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1086

Abstract

This study examines the role of Search Engine Optimization (SEO) in supporting digital business growth within an increasingly competitive online environment. As digital transformation accelerates, many businesses continue to face challenges related to limited online visibility, low search engine rankings, and intense market competition. To address these issues, this research investigates the influence of four key SEO dimensions keyword optimization, content quality, technical SEO, and backlink strategy on digital business growth, measured through website traffic, brand visibility, customer engagement, and online sales performance. A quantitative research approach was employed, with data collected through structured questionnaires distributed to business owners and digital marketing practitioners and analyzed using multiple regression analysis. The results indicate that SEO significantly contributes to digital business growth, with content optimization demonstrating the strongest positive effect (β = 0.312, p < 0.001), followed by technical SEO (β = 0.287, p = 0.001) and backlink strategy (β = 0.254, p = 0.003). Furthermore, the regression model explains 55.1% of the variance in digital business growth (R² = 0.551), indicating substantial predictive capability. These findings suggest that integrated SEO practices enhance online visibility, attract potential customers, increase customer engagement, and improve sales performance. Therefore, SEO should be regarded as a strategic component of digital marketing initiatives that enables businesses to strengthen competitiveness, support sustainable growth, and achieve long-term success in the evolving digital marketplace
Analysis of Digital Marketing through Social Media for Company Brand Image Dwi Andayani; Aulia Khanza; Tyco Fauzun Azhar; Maevi Chan
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1167

Abstract

This study aims to analyze digital marketing activities through social media in building brand image in construction companies. The study focuses on the company’s official Instagram and TikTok accounts by examining digital marketing activities, including project documentation, promotional and educational content, operational activities, audience interactions, content creation, upload consistency, visual presentation, and the delivery of company service information. The study used a qualitative descriptive approach with a case study method. Data were collected through observation and documentation of the company’s social media activities during fieldwork. Then, they were analyzed descriptively based on content consistency, visual identity, audience interaction, and the role of digital content in shaping brand image. The research results show that social media plays a crucial role in strengthening a company’s brand image. Visual content, including project documentation, operational activities, educational content, and service information, appeared to contribute to building a professional and credible corporate image. Furthermore, visual consistency across content supports audience recognition of the company’s identity. This study concludes that planned, consistent social media management supported by quality content is an efective strategy for construction companies in improving brand image, strengthening credibility, and expanding business opportunities in the digital era.
Data Mining Techniques in Blockchain Using Machine Learning Algorithms Ankur Singh Bist; Aswadi Jaya; Agung Rizky; Maulana Arif Komara; Kgomotso Moyo
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1169

Abstract

The rapid advancement of blockchain technology has generated an enormous volume of complex transaction data, creating significant challenges in data analysis, particularly in terms of scalability, noise, and anonymity. This study aims to identify effective data mining techniques and implement machine learning algorithms to enhance the performance of blockchain data analysis. A quantitative approach was employed by utilizing data mining techniques and machine learning algorithms, including Random Forest, K-Means, and Neural Network. These methods were applied to blockchain datasets obtained from Ethereum, Bitcoin, and OpenSea through several stages, namely preprocessing, feature engineering, model training, and evaluation using accuracy, precision, recall, F1-score, and Root Mean Square Error metrics. The results indicate that Random Forest demonstrates stable performance with high classification accuracy, Neural Network excel at capturing complex patterns in non-linear data, while K-Means is effective in identifying patterns through clustering. These findings suggest that each algorithm offers distinct advantages depending on the characteristics of the data and the objectives of the analysis. This study concludes that the integration of data mining techniques and machine learning algorithms can significantly improve the effectiveness of blockchain data analysis compared to traditional methods. Furthermore, the proposed integrated framework can serve as a reference for the future development of blockchain-based data analytics systems. Rather than providing a quantitative benchmark against conventional analytical approaches, this study proposes a standardized methodological framework intended to support consistent implementation, evaluation, and future comparative validation across heterogeneous blockchain analytics applications.
A Literature Review of Smart Contract Performance Across Blockchain Environments Dwi Cahyono; Shofiyul Millah; Franses Gabriela Barasa; Yasir Mustafa Kareem
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1176

Abstract

Smart contracts have become an important component of blockchain ecosystems because they enable automated, transparent, and decentralized digital processes. However, their performance varies across blockchain environments due to differences in architecture, consensus mechanisms, transaction costs, scalability, security, governance, and interoperability. Existing studies often examine isolated performance indicators or individual blockchain platforms, limiting comprehensive cross-platform understanding. This study aims to comparatively analyze smart contract performance across major blockchain platforms, identify technical and contextual factors influencing performance, and synthesize emerging research trends and future research opportunities. A Structured Literature Review was conducted using literature obtained from Scopus, IEEE Xplore, ACM Digital Library, SpringerLink, ScienceDirect, and Google Scholar. Peer-reviewed English publications from 2020–2026 were selected through a PRISMA-based screening process. The reviewed studies were systematically analyzed based on blockchain platforms, application domains, performance metrics, security, governance, scalability, and interoperability. The review identifies Ethereum, BNB Chain, Solana, Polygon, Hyperledger Fabric, and Avalanche as major platforms with distinct performance characteristics and trade-offs. Throughput, latency, transaction cost, and scalability are prominent technical dimensions, while security, governance, and interoperability provide essential contextual perspectives. The findings indicate that no single platform consistently provides superior performance across all application requirements. Smart contract performance should be evaluated using a multidimensional approach rather than a single technical indicator. Future research should emphasize interoperability, Layer-2 scalability, cross-chain smart contracts, security assurance, and governance to support more comprehensive blockchain performance evaluation.
Analyzing Intelligent Smart Contract Effectiveness in Blockchain Based Digital Marketing Ecosystems Raden Roro Ayu Metarini; Nuke Puji Lestari Santoso; Mitra Trima Des Sincer Putri; Marta Rodriguez
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1186

Abstract

The rapid advancement of blockchain technology has accelerated the adoption of intelligent smart contracts across various sectors due to their ability to automate transactions, enhance operational efficiency, and reduce dependence on intermediaries. However, the effectiveness of intelligent smart contracts within digital marketing ecosystems remains influenced by technical and operational factors such as automated adspend execution and fraud prevention. This study aims to explore the determinants of Intelligent Smart Contract Effectiveness in blockchain-based digital marketing systems by examining the effects of Security Capability, Interoperability, Scalability, Transparency, Trustworthiness, and Automation Intelligence. A quantitative approach was employed, with data collected through questionnaires distributed to respondents with knowledge and experience related to blockchain technology. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software. The findings indicate that all examined variables have positive and significant effects on Intelligent Smart Contract Effectiveness. Among these variables, Automation Intelligence exhibits the strongest influence, highlighting the critical role of intelligent automation and adaptive decision-making in improving smart contract performance. Furthermore, Security Capability, Interoperability, Scalability, Transparency, and Trustworthiness also significantly contribute to the successful implementation of intelligent smart contracts. The study concludes that the effectiveness of intelligent smart contracts in decentralized blockchain systems is determined by the combined effects of security, interoperability, scalability, transparency, trustworthiness, and automation intelligence. These findings provide both theoretical and practical contributions to blockchain research and offer valuable insights for organizations and developers seeking to improve the effectiveness of intelligent smart contract implementation across various industries.
Blockchain Adoption for Secure Digital Payments in Modern Business Ecosystems Ihsan Nuril Hikam; Ahmad Gunawan; Sheila Aulia Anjani; Jonathan Parker
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1166

Abstract

The rapid growth of digital commerce has significantly increased the demand for secure and reliable digital payment systems within modern business ecosystems. Traditional centralized payment infrastructures often face challenges related to security vulnerabilities, fraud risks, and limited transparency, which may reduce user trust and create risks for financial transactions. Therefore, this study aims to analyze blockchain adoption as a solution to enhance security, transparency, and reliability in digital payment systems in contemporary business environments. This research applies a quantitative research approach by examining the relationships between several key variables, including perceived security, trust, technological readiness, and regulatory support, as independent variables influencing blockchain adoption as the dependent variable. Data are analyzed through a structured research framework supported by statistical evaluation to understand the influence of these factors on blockchain adoption in digital payment systems. The findings indicate that perceived security, trust, technological readiness, and regulatory support positively influence the blockchain adoption. Blockchain’s decentralized architecture improves transaction transparency, strengthens data protection, and reduces the risks associated with fraud and data manipulation in digital financial transactions. Overall, the study concludes that blockchain technology has strong potential to enhance the security, transparency, and efficiency of digital payment systems in modern business ecosystems, while the development of technological infrastructure, supportive regulatory frameworks, and increased user trust are essential to promote wider adoption of blockchain-based financial technologies in the evolving digital economy.
Managing Data Complexity in Blockchain-Based Workflow Systems Neng Ayu Sri Wahyuni; Fitra Putri Oganda; Sherli Triandari; Nyree Ani
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1179

Abstract

Blockchain-based workflow systems provide transparency, security, and data integrity. However, increasing data volume, variety, and velocity create complexity that can affect workflow efficiency, system scalability, and resource utilization. This study aims to develop a framework for managing data complexity while improving workflow efficiency through integrated data management and workflow optimization. A conceptual design approach is adopted by developing a layered architecture consisting of the data, blockchain, and application layers. The framework is conceptually evaluated through data complexity analysis based on volume, variety, and velocity and their effects on workflow efficiency and resource management. The proposed framework integrates data classification and prioritization, where high-priority data are processed on the blockchain, while low-priority data are stored off-chain. Data pruning, compression, smart contracts, and priority-based task scheduling are incorporated to reduce redundancy, optimize storage capacity, improve data access speed, and accelerate workflow execution. The integration of data management and workflow processes also helps minimize potential bottlenecks. Compared with previous studies, the framework provides a more integrated approach by combining data complexity management and workflow optimization within a single model. Conceptually, it has the potential to improve efficiency, scalability, and system effectiveness. In addition, the framework establishes a structured basis for future prototype development, simulation, and empirical testing across diverse blockchain workflow scenarios and operational conditions effectively. However, prototype implementation and empirical evaluation are required to quantitatively validate its performance.
Blockchain Applications for Academic Credential Verification in Higher Education Herman Herman; Adam Faturahman; Steven Harazaki Lase; Kristina Vaher
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1195

Abstract

The rapid digitalization of higher education has brought about a greater demand for academic credential verification systems that are secure, dependable, and efficient. Conventional verification methods typically depend on centralized databases and manual procedures, which can lead to security risks, delays in administration, and chances for credential forgery. Blockchain technology has gained attention as a promising solution, as its decentralized architecture, cryptographic mechanisms, and tamper-resistant ledger enable more reliable and trustworthy credential management. This study aims to systematically review blockchain applications for academic credential verification in higher education and identify key technological benefits, implementation challenges, and emerging. A Systematic Literature Review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify research directions. Relevant studies published between 2022 and 2026 were identified from Scopus, IEEE Xplore, ScienceDirect, and Springer- Link. From 125 initial records, 25 studies met the predefined inclusion and exclusion criteria and were included in the qualitative synthesis. The reviewed studies indicate that blockchain can enhance credential security, authenticity, transparency, and verification efficiency while reducing administrative burdens and credential fraud. The reviewed studies also highlight the use of permissioned and consortium blockchains, smart contracts, Decentralized Identity, Verifiable Credentials, and off-chain storage to support privacy and system performance. However, scalability, interoperability, regulatory compliance, privacy, implementation costs, and technical expertise remain significant barriers. These findings highlight blockchain’s potential to support sustainable digital transformation and enhance the reliability, efficiency, and trustworthiness of academic credential verification in higher education.
Automating Hazardous Gas Mitigation in Enclosed Areas Using Smart Contracts and Sensors Michael Surya Gunawan; Ridwan Kurniaji; Abdul Hamid Aribathi; Untung Rahardja; Lokae Fern
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1200

Abstract

Hazardous gas exposure in confined work environments, including mines, tunnels, and petrochemical facilities, threatens workers because conventional monitoring can experience communication attenuation, sensor faults, delayed response, and false alarms. Recent studies have advanced IoT gas sensing, LoRa communication, machine-learning-based fault detection, and spatiotemporal prediction, while blockchain and smart contracts have been explored for data integrity and rule-based automation. However, these capabilities remain fragmented. Existing systems rarely integrate reliable wireless sensing, sensor-fault validation, AI-based gas prediction, trusted safety verification, automated mitigation, and auditable event recording within one framework. This study aims to develop and experimentally evaluate a smart-contract enabled Networked Intelligent Gas Sensor System (N-IGSS) for real-time hazardous-gas monitoring and mitigation. The system combines portable MOX gas sensors, LoRa 868 MHz communication, hybrid HMM-ANN fault detection, and Spatial-Temporal Attention Network (STAN) analysis with a proposed blockchain and smart-contract mechanism for safety-event verification, authorization, and traceability. The framework extends conventional IoT monitoring by connecting validated sensor observations and AI outputs with predefined smart-contract safety rules and automated actuators, including ventilation, alarms, and gas valves. Experimental results show LoRa communication up to 590 meter, low false-positive HMM-ANN fault detection, and strong STAN performance for gas prediction and localization. The system supports notification and automated mitigation, providing foundation for safer, more responsive, and traceable occupational safety management.
Digital Banking Adoption and MSMEs Resilience in Blockchain Enabled Financial Ecosystems Imam Ryan Maulana; Abdul Hamid Arribathi; Richard Evans
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1203

Abstract

The growing adoption of digital financial technologies has provided Micro, Small, and Medium Enterprises (MSMEs) with opportunities to improve financial management and resilience within emerging blockchain-enabled financial ecosystems. However, digital banking adoption does not necessarily ensure that technological access will result in stronger financial resilience. Previous studies have commonly examined digital banking adoption, financial literacy, and financial resilience independently, leaving limited understanding of how these factors interact through financial management practices and financial capabilities. This study investigates the influence of Digital Banking Adoption on MSMEs’ Financial Resilience, with Financial Planning serving as a mediating mechanism and Financial Literacy as a moderating factor. The novelty of this study lies in developing an integrated behavioral and financial capability framework that connects digital banking adoption with MSMEs’ financial resilience while considering blockchain-enabled financial ecosystems as the broader technological context. A quantitative cross-sectional design was employed using data from 300 MSMEs owners or managers in Indonesia who actively use digital banking services. The data were analyzed using PLS-SEM. The results show that Digital Banking Adoption significantly affects Financial Planning (β = 0.72, p < 0.001) and Financial Resilience (β = 0.24, p = 0.003). Financial Planning significantly affects Financial Resilience (β = 0.48, p < 0.001) and mediates the relationship (β = 0.35, p < 0.001). Financial Literacy negatively moderates the relationship (β = −0.18, p = 0.015), suggesting that higher financial literacy may reduce digital banking’s marginal contribution to resilience.

Page 1 of 1 | Total Record : 10

 1 

Filter by Year

2027 2026


Reset
Filter By Issues
All Issue Vol. 6 No. 2 (2027): Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology Vol. 5 No. 2 (2026): Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology Vol. 4 No. 2 (2025): Blockchain Frontier Technology Vol. 4 No. 1 (2024): Blockchain Frontier Technology Vol. 3 No. 2 (2024): Blockchain Frontier Technology Vol. 3 No. 1 (2023): Blockchain Frontier Technology Vol. 2 No. 2 (2023): Blockchain Frontier Technology Vol. 2 No. 1 (2022): Blockchain Frontier Technology Vol. 1 No. 2 (2022): B-Front(Blockchain Frontier Technology) Vol. 1 No. 01 (2021): B-Front(Blockchain Frontier Technology) More Issue