Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
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All Journal International Journal of Research and Applied Technology (INJURATECH)
Hasan, Mochammad Fuad
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Data Security and Policy Management in E-Government Cloud Platforms: A Systematic Review of Challenges and Opportunities in Archipelagic Nations Hasan, Mochammad Fuad
International Journal of Research and Applied Technology (INJURATECH) Vol. 4 No. 2 (2024): Vol 4 No 2 (2024)
Publisher : Universitas Komputer Indonesia

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Abstract

The adoption of cloud computing in e-government offers significant scalability but presents unique architectural and regulatory complexities for archipelagic nations due to geographical fragmentation. This systematic literature review investigates the intersection of cloud data security, policy management, and topographical constraints. Following the PRISMA protocol, we analyzed 42 peer-reviewed articles (2019–2026) from Scopus, IEEE Xplore, and ScienceDirect. The findings reveal a critical "archipelagic latency trap," physical infrastructure vulnerabilities at edge nodes, and significant ambiguities in distributed data sovereignty across local autonomous jurisdictions. Existing centralized security frameworks are proven inadequate for these decentralized topologies. Consequently, we propose the necessity of an Archipelagic Cloud Governance Framework integrating Hybrid Edge-Cloud architectures and Consortium Blockchain technologies. This approach mitigates inter-island synchronization failures while ensuring immutable audit trails and regulatory compliance. Ultimately, this study provides a foundational roadmap for policymakers engineering resilient, geographically-adapted public service infrastructures.
Security and Privacy Challenges of AI Deployment in Cloud Computing: A Systematic Literature Review Hasan, Mochammad Fuad
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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The rapid adoption of artificial intelligence (AI) within cloud computing environments has introduced significant security and privacy challenges that demand systematic examination. This study presents a systematic literature review on security and privacy challenges in deploying Artificial Intelligence (AI) within cloud computing environments. The integration of AI and cloud platforms enables scalable intelligent services across various domains, but also introduces significant risks, including data leakage, insecure APIs, model extraction, adversarial attacks, and privacy inference threats. Following PRISMA-inspired guidelines, relevant studies published between 2019 and 2025 were systematically identified from major academic databases and analyzed using thematic synthesis. The review categorizes key security and privacy threats, summarizes commonly adopted mitigation strategies, and examines cloud deployment architectures for AI workloads. The findings indicate that existing solutions are largely fragmented and often focus on isolated technical mechanisms without providing end-to-end security integration. Moreover, trade-offs between privacy preservation, system performance, scalability, and operational cost remain insufficiently addressed. This paper highlights critical research gaps and outlines future research directions toward building trustworthy, secure, and privacy-aware AI systems in cloud computing environments
Integration of GIS and Remote Sensing for Environmental Monitoring: A Systematic Literature Review Hasan, Mochammad Fuad
International Journal of Research and Applied Technology (INJURATECH) Vol. 4 No. 2 (2024): Vol 4 No 2 (2024)
Publisher : Universitas Komputer Indonesia

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Abstract

The integration of Geographic Information Systems (GIS) and Remote Sensing (RS) has become essential for addressing escalating global environmental challenges. This systematic literature review, strictly adhering to PRISMA guidelines, synthesizes 115 peer-reviewed articles published between 2016 and 2026 to evaluate the current state, methodological trends, and technological synergies in environmental monitoring. Our findings reveal that Forestry and Land Use/Land Cover (LULC) change, alongside water resource and disaster management, are the predominant application domains. Crucially, the review highlights a significant paradigm shift from traditional analytical methods to advanced multi-sensor data fusion and the rapid incorporation of Artificial Intelligence (AI) and Machine Learning algorithms, which drastically enhance spatial predictive accuracy. Despite these advancements, challenges such as massive geospatial data handling and sensor interoperability remain prevalent. Ultimately, this study provides a comprehensive framework for researchers and policymakers, emphasizing that leveraging cloud computing and AI-driven GIS-RS synergies is vital for formulating robust, data-driven environmental conservation and disaster mitigation strategies.
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