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All Journal Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC)
Muchlisina Madani
University of Raharja
Computer Science & IT Control & Systems Engineering Education Library & Information Science

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Leveraging IPFS for Secure, Distributed Blockchain Data Infrastructure and Enhanced Security Sandy Setiawan; Muchlisina Madani; Sondang Visiana S; Elisa Ananda Natalia; Novita Khairunnisa; Kristina Vaher
Blockchain Frontier Technology Vol. 5 No. 1 (2025): Blockchain Frontier Technology
Publisher : Indonesian Association of Higher Education in Informatics and Computing (APTIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i1.826

Abstract

In an increasingly digital world, where centralized storage systems dominate and censorship risks are growing, the InterPlanetary File System (IPFS) has emerged as a promising decentralized data storage solution. This research aims to evaluate the potential and challenges of implementing IPFS, using a descriptive qualitative approach that includes both a comprehensive literature review and technical simulations. The literature review highlights IPFS’s advantages, particularly in areas such as data integrity, resistance to censorship, and efficient content distribution. However, it also identifies key challenges, such as high latency and the dependency on node availability. To further investigate these issues, technical simulations were conducted using a private IPFS network, testing file access latency under different network conditions. The results indicate that the fastest average latency occurs when all nodes are active, at 150 ms, while the highest latency is observed when files are accessed through a public gateway, with an average of 540 ms. These findings demonstrate that IPFS has substantial potential to create a more open, decentralized digital ecosystem that resists centralized control. However, for large-scale adoption to be feasible, significant improvements in infrastructure, particularly node availability and latency management, are required to fully support IPFS’s widespread implementation.
Life Cycle Assessment of Silicon Photovoltaics and Their Environmental Impacts Lukmanul Hakim Aziz; Brigitta Callula; Achmad Rozi; Muchlisina Madani
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.941

Abstract

The rapid expansion of silicon based Photovoltaic (PV) technologies continues to drive the global shift toward sustainable energy systems. However, the environmental implications across the full life cycle of PV modules particularly those associated with upstream silicon purification routes remain insufficiently examined. This study provides a comprehensive assessment of the environmental and process level impacts of Metallurgical Grade Silicon (MGS) and Upgraded Metallurgical Grade Silicon (UMGS), covering extraction, manufacturing, operation, and end of life stages. A process oriented Life Cycle Assessment (LCA) is conducted to analyze variations in carbon intensity, hazardous material use, and energy demand, complemented by comparative evaluations of monocrystalline and polycrystalline module production pathways. To enhance analytical precision, this study incorporates an AI-assisted predictive modeling framework using supervised machine learning to estimate Global Warming Potential (GWP) and identify key factors influencing emission variability. The AI-enhanced model reveals that electricity mix and purification route exert the strongest influence on GWP, and scenario simulations demonstrate that UMGS based processes can reduce upstream emissions by up to 89% under favorable energy conditions. Additionally, the study highlights future challenges related to increasing PV waste volumes between 2025 and 2030 and the need for improved recycling infrastructures. Overall, the integration of AI-based prediction with conventional LCA offers a more dynamic and adaptive evaluation of PV sustainability performance. The findings underscore the importance of renewable powered manufacturing, early adoption of low-energy purification technologies, and policy support to achieve long-term environmental and socio-economic benefits.
Co-Authors Achmad Rozi Brigitta Callula Elisa Ananda Natalia Kristina Vaher Lukmanul Hakim Aziz Novita Khairunnisa Sandy Setiawan Sondang Visiana S