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INDONESIA
International Journal of Research and Applied Technology (INJURATECH)
Published by Universitas Komputer Indonesia
ISSN : 28100662     EISSN : 28077229     DOI : https://doi.org/10.34010/injuratech.v1i2.5902
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
INJURATECH cover all topics under the fields of Computer Science, Information system, and Applied Technology. Scope: Computer Based Education Information System Database Systems E-commerce and E-governance Data mining Decision Support System Management Information System Social Media Analytic Data visualization Cloud computing platforms Distributed file systems and databases Big data technologies Data capture and storage Computer Architecture and Embedded Systems Geographic information system (GIS) Remote Sensing Software Engineering Internet and Web Applications Mobile Computing Hardware and physical security Mobile Computing Security management and policies Block chain Technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 251 Documents
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A Systematic Literature Review of User Acceptance Factors in E-Government Services Sari, Annisa Wulan
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 rapid digital transformation in the public sector has led to the widespread implementation of e-government services. However, the success of these systems heavily depends on citizen adoption and persistent usage. This study aims to explore and analyze the critical factors influencing user acceptance of e-government services through a qualitative approach. The thematic analysis reveals that user experiences closely align with the core constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). Key determinants driving adoption include performance expectancy, social influence, and a strong foundational trust in government, which emerged as a pivotal factor for users in developing regions. Furthermore, the qualitative findings highlight significant real-world challenges regarding the accessibility of e-government platforms for elderly and disabled users. These insights provide a strategic roadmap for policymakers and developers to enhance inclusive and user-centric digital public services.
User Privacy in the Age of Mobile Browsing: A Literature Review of Data Tracking and Protection Policies Karin, Juliana
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 rapid evolution of mobile computing has transformed the smartphone into a primary gateway for internet access, simultaneously turning it into a rich source of granular personal data. This literature review examines the current landscape of user privacy within mobile browsing environments, focusing on the sophisticated mechanisms of data tracking and the efficacy of modern protection policies. As mobile browsers integrate more deeply with OS-level sensors and location services, the surface area for unauthorized data harvesting has expanded beyond traditional web cookies to include browser fingerprinting and cross-app tracking. This paper synthesizes recent research to evaluate the tension between personalized web experiences and the fundamental right to privacy. We analyze the impact of major regulatory frameworks, such as GDPR and CCPA, against the technical reality of "shadow tracking." Our findings suggest that while policy awareness is increasing, technical enforcement remains inconsistent, leaving mobile users vulnerable to opaque data practices.
Explainable AI (XAI) for Fake News Detection: A Review of Interpretability in Deep Learning Models for Misinformation Classification Munawaroh, Silvi
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

This study provides a comprehensive review of Explainable AI (XAI) applications in fake news detection, addressing the critical "black-box" nature of deep learning models used for misinformation classification. We systematically analyze various interpretability techniques, categorized into ante-hoc and post-hoc methods, applied to neural architectures such as CNNs, RNNs, and Transformers. The study evaluates how these techniques extract linguistic, social context, and visual features to justify classification outcomes. The findings reveal that while attention mechanisms and gradient-based explanations improve transparency, there remains a significant trade-off between model complexity and explanatory clarity. The discussion highlights the challenges of "explanation consistency" and the susceptibility of interpretability tools to adversarial attacks. We conclude that integrating XAI is essential for fostering user trust and regulatory compliance. Future research should prioritize human-centric evaluations to ensure that AI-generated explanations are cognitively accessible to non-expert end-users.
Access Control and Security Monitoring in Blockchain-Based Cloud Information Systems: A Systematic Review Hayati, Euis Neni
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 blockchain technology into cloud information systems has emerged as a promising approach to enhance data transparency, trust, and security. However, the transition toward a decentralized and distributed architecture introduces novel challenges, particularly concerning the enforcement of access control and security monitoring mechanisms within cloud environments. This study presents a systematic literature review focusing specifically on the access control models and security monitoring strategies implemented in blockchain-based cloud systems. Based on the analysis of recent peer-reviewed studies filtered through a structured methodology, the findings indicate that smart contract-driven Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and Capability-Based Access Control (CapBAC) are the dominant approaches for autonomous authorization management. In terms of security monitoring, blockchain-enabled audit logs have proven to provide a high degree of traceability and absolute tamper resistance, effectively mitigating malicious insider threats. Despite these significant advantages, this review identifies that scalability issues, high network latency, and computational costs remain critical bottlenecks for industrial-scale adoption. Consequently, this review highlights current research gaps and recommends future research directions, including the implementation of off-chain scaling solutions, Zero-Knowledge Proofs (ZKPs) for enhanced privacy
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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Abstract

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
A Literature Review on Resource-Efficient Web Browsing in Low-End Mobile Computing Environments Karin, Juliana
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

The proliferation of mobile computing has bridged the digital divide, yet a significant portion of the global population relies on low-end mobile devices characterized by limited CPU power, RAM, and battery life. This paper provides a comprehensive literature review on resource-efficient web browsing strategies tailored for these constrained environments. As web applications become increasingly complex with heavy JavaScript frameworks and high-resolution media, the performance gap between high-end and low-end devices widens. We analyze current optimization techniques, including cloud-assisted browsing, code offloading, and lightweight browser architectures. The review identifies critical bottlenecks in memory management and energy consumption that current solutions struggle to address. By synthesizing recent research, this paper outlines the shift toward "edge-aware" browsing and progressive enhancement as vital strategies. Our findings suggest that while hardware-centric optimizations are plateauing, software-driven efficiency remains the primary frontier for ensuring inclusive digital access for users in developing technological landscapes
The Role of Cloud Computing and Big Data in Enhancing E-Learning Service Quality Sari, Annisa Wulan
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

The transition to digital education has exponentially increased the demand for robust, scalable, and personalized e-learning platforms. Legacy educational systems often struggle with server overloads, limited storage capacity, and the inability to process massive amounts of student data. This study explores the integration of Cloud Computing and Big Data analytics as a strategic solution to enhance e-learning service quality. Through a qualitative approach and thematic analysis of recent literature, this paper identifies that Cloud Computing provides a highly scalable, cost-effective infrastructure that ensures continuous system availability. Concurrently, Big Data empowers educational institutions to analyze student learning behaviors, predict academic outcomes, and deliver personalized learning experiences. The findings suggest that the synergy between these two technologies not only resolves technical bottlenecks but also transforms passive e-learning environments into adaptive, student-centric ecosystems. This study provides a comprehensive framework for higher education institutions aiming to modernize their IT governance and instructional delivery.
Cross-Domain Sentiment Analysis using Transfer Learning: A Literature Review on Natural Language Model Adaptation from Social-Media to Macroeconomic Indicator Prediction Munawaroh, Silvi
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

This study reviews the efficacy of transfer learning in adapting sentiment analysis from social media domains to macroeconomic indicator prediction. The study evaluates existing literature on natural language model architectures, specifically Transformer-based models, performing domain adaptation from informal social media discourse to formal economic contexts. Findings indicate that pre-trained models significantly enhance predictive accuracy for data-scarce economic indicators by capturing real-time public perception. While effective in addressing labeled data sparsity, primary challenges involve linguistic noise and inherent demographic biases within social media datasets. Transfer learning serves as a critical bridge in transforming public sentiment into predictive economic signals. This cross-domain approach provides a dynamic, supplementary instrument for policymakers to monitor macroeconomic fluctuations through digital behavioral patterns.
Encrypted Data Toward Finance Security in Indonesia Literature Review Study Meliala, Brandon Nathanael
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

This study examines the role of data encryption in strengthening financial security in Indonesia through a literature review approach. Rapid growth of digital banking, fintech services, and cashless transactions has increased exposure to cyber threats such as data breaches, identity theft, and financial fraud. By synthesizing findings from national and international journals, regulations, and industry reports, this article analyses types of encryption used in financial systems, including symmetric and asymmetric algorithms, end-to-end encryption, and key management practices. The review highlights that encryption significantly reduces the risk of unauthorized access and supports compliance with regulatory frameworks on data protection and financial stability. However, challenges remain in implementation, such as limited technical capacity, high operational costs, and uneven security awareness among institutions and users. This study concludes that effective encryption strategies, combined with governance and user education, are essential to enhance trust and resilience in Indonesia’s financial sector in the long term.

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