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p-Index From 2021 - 2026
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All Journal Blockchain Frontier Technology (BFRONT)
Chua Toh Hua
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Library & Information Science

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Enhancing Service Quality and Student Loyalty in Higher Education Using Blockchain Technology Ayun Maduwinarti; I.G.N. Andhika Mahendra; Dwi Cahyono; Cristino Gusmao; Chua Toh Hua
Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i1.843

Abstract

In the increasingly digital era demanding transparency, blockchain emerges as a technology with significant potential to support higher education services. This system offers security, efficiency, and decentralization in managing academic data and certifications. This study aims to examine the role of blockchain in improving service quality and student loyalty. Data were collected through interviews and FGDs with participants from students, faculty, and administrative staff relevant to the technology's implementation in their institutions. The findings show positive acceptance of blockchain, especially in terms of transparency and service speed. Participants also suggested digital incentives through a token system as a way to encourage active student engagement. However, challenges such as infrastructure, technological literacy, and regulations remain major obstacles. These results reinforce that blockchain can improve service quality and create loyalty based on a fair and measurable system.
Utilizing Blockchain for Trustworthy and Transparent AI Decision Making Herman Herman; Rohim Rohim; Rizki Indrawan; Chua Toh Hua
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.v6i1.1031

Abstract

The increasing adoption of AI in critical sectors such as healthcare, finance, transportation, and public services raises significant challenges related to transparency, accountability, and trust in automated decision-making processes, particularly since many AI models still operate as black boxes that are difficult to interpret and audit. This study investigates the potential of integrating blockchain technology to enable trustworthy and transparent AI decision-making and is conducted under the framework to systematically design, implement, and evaluate the proposed solution. The proposed framework records AI inference results and relevant metadata onto the blockchain through smart contracts to ensure data immutability and traceability. A prototype system is developed and evaluated using a mixed-method approach, combining qualitative analysis of transparency and auditability with quantitative measurements of system performance such as latency and overhead. The results demonstrate that blockchain integration significantly enhances auditability, data integrity, and user trust compared to conventional AI systems. However, several limitations are identified, including scalability issues, transaction costs, and increased latency caused by on-chain recording processes. Despite these challenges, the proposed approach shows strong potential to improve the accountability of AI systems in high-risk environments and contributes a practical framework along with empirical insights for organizations seeking to adopt transparent and reliable AI, while also opening opportunities for further development through architectural optimization and the adoption of layer-2 blockchain technologies.
Decentralized Storage in Smart City Data Infrastructure SWOT Analysis Nuraeni, Rani; Elisa Ananda Natalia; Chua Toh Hua; Nanda Septiani; Ipang Sasono
Blockchain Frontier Technology Vol. 5 No. 2 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i2.872

Abstract

The rapid growth of data volume and complexity in modern urban environments has created a critical need for storage systems that are secure, scalable, and resilient. This background emphasizes the urgency of adaptive data infrastructure to support smart city development. This study aims to provide a comprehensive SWOT analysis of decentralized storage in strengthening smart city data infrastructure. A qualitative descriptive-analytical approach is employed, using systematic literature review and document analysis to identify key internal and external strategic factors. The findings reveal key strengths, including enhanced data security, high resilience, and scalability. However, weaknesses such as implementation complexity, latency issues, and dependency on network stability are also noted. Opportunities lie in the integration with Internet of Things (IoT) ecosystems, growing public awareness of data privacy, and emerging collaborative economic models. Meanwhile, threats include regulatory ambiguity, lack of standardization, and evolving cybersecurity risks. This study contributes a strategic framework to assist policymakers, urban planners, and technology stakeholders in integrating decentralized storage systems into smart city architectures. In alignment with the Sustainable Development Goals (SDGs), particularly Goal 11 (Sustainable Cities and Communities) and Goal 9 (Industry, Innovation, and Infrastructure), the research highlights the importance of secure, inclusive, and adaptive digital infrastructure in advancing sustainable urban development.
Co-Authors Ayun Maduwinarti Cristino Gusmao DWI CAHYONO Elisa Ananda Natalia Herman Herman I.G.N. Andhika Mahendra Ipang Sasono Nanda Septiani NURAENI, RANI Rizki Indrawan Rohim Rohim