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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 20 Documents
 1   2 
Search results for , issue "Vol. 5 No. 2 (2025): December 2025" : 20 Documents clear
Physics-Informed Artificial Intelligence for Adaptive Wireless Channel Modelling in Fifth-Generation (5G) Networks Muhammed, Aniru Abudu; Muhammed, Hibah
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

Accurate wireless channel modeling is fundamental to the design and optimization of fifth-generation (5G) communication systems. Traditional geometry-based stochastic models (GBSMs) and empirical formulations, while effective in static environments, often fail to capture the nonlinear, non-stationary, and environment-dependent propagation behaviours inherent in modern multi-antenna and millimeter-wave systems. This study introduces a physics-informed AI hybrid framework that fuses physical propagation principles with deep learning architectures, enabling channel modeling that is interpretable, adaptive, and data-efficient. Using large-scale datasets including DeepMIMO, COST (Cooperation in Science and Technology) 2100, and New York University (NYU) Wireless, the model integrates Physics-Informed Neural Networks (PINNs) and Convolutional Neural Networks (CNNs) to simultaneously capture spatial, temporal, and frequency-domain relationships under realistic propagation environments. Reinforcement and federated learning layers enable real-time adaptation and decentralized training across multiple base stations while preserving data privacy. Experimental results demonstrate substantial improvements over benchmark models such as 3GPP (3rd Generation Partnership Project) TR 38.901, COST 2100, and QuaDRiGa  (QUAsi Deterministic RadIo Channel GenerAtor), achieving an RMSE of 1.72 dB and NMSE of –20.6 dB, corresponding to a 25–30% accuracy gain. Visual analyses of power delay profiles, residual error distributions, and spatial correlation maps confirm the model’s robustness and physical consistency. The proposed framework offers a scalable, interpretable, and adaptive paradigm for next-generation wireless channel modeling, paving the way toward intelligent, self-optimizing, and 6G-ready communication networks that bridge the gap between physics-based theory and AI-driven modeling.
Integration Of Hirka Packaging As A Physical Output Of The System E-Commerce In Improving Customer Experience Fadillah, Ismail Hudan; Soegoto, Eddy Soeryanto; Wahdiniwaty, Rahma; Sumitra, Irfan Dwiguna; Bachtiar, Adam Mukharil
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 development of e-commerce as an applied information system has changed the interaction pattern between brands and consumers, where user experiences are increasingly mediated by non-physical digital processes. This condition creates limitations in conveying material value, product quality, and brand character, especially for products that emphasize material aspects and an artisan approach. This study aims to analyze the role of packaging as a physical output in the e-commerce system architecture and its contribution to enhancing the customer experience value of the local leather shoe brand HIRKA. The study uses a qualitative approach with a case study method. Data collection was carried out through observations of the marketplace system and HIRKA packaging design, in-depth interviews with brand owners, and literature studies related to e-commerce information systems and technology-based customer experience. The results show that packaging functions as an extension of the information system that translates data, visual representations, and digital narratives into a physical post-purchase experience. The integration between the e-commerce system and packaging design creates continuity between the digital process and the physical output, narrowing the gap in user experience, and increasing customer perceptions of value, trust, and satisfaction. These findings emphasize that evaluation of e-commerce system performance needs to consider the quality of integration between the digital system and the physical output as part of the overall customer experience.
Indonesian Oil and Gas Export Data Forecasting Using Autoregressive Integrated Moving Average and Exponential Triple Smoothing Methods Kurniawan, Deni; Afrianto, Irawan
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 analysed historical data movement patterns and forecasted the value of oil and gas exports for the next 12 periods. The data obtained was secondary data in the form of monthly time series for the period (2021–2025). A time series is a series of observations of a variable that occur in relation to the time of its occurrence, while time series data is data collected over a specific time period. The analysis method used was the Box-Jenkins method or Autoregressive Integrated Moving Average with the help of R software. The model obtained through the stages of model identification, parameter estimation, and diagnostic testing was then used to project the data. The best model was selected based on the smallest Akaike Information Criterion (AIC) value and valid parameter significance tests. The forecast results for 2026 show a trend that tends to be constant or flat following the latest data level, with a confidence interval that widens as the time period increases. This indicates that the value of oil and gas exports is predicted to be stable but carries a high risk of uncertainty in the future, thus requiring adaptive policy anticipation to address market volatility.
The Role of Visual Identity Design and Digital Technology in Developing Local Photography Studio Entrepreneurship: A Case Study of Natsume Studio Foto Cianjur Akbar, Aldi Mohamad; Soegoto, Eddy Soeryanto; Wahdiniwaty, Rahma; Sumitra, Irfan Dwiguna; Bachtiar, Adam Mukharil; Mohamad Akbar, Aldi
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 growth of digital technology has reshaped entrepreneurial practices in the creative industry, including local photography studios. However, many creative MSMEs have not yet optimized visual identity design and digital media as strategic business assets. This study examines the role of visual identity design and digital media in supporting entrepreneurial development within a local photography studio. Using a qualitative case study approach, data were collected through visual observation, semi- structured interviews, and documentation of promotional media. The findings show that consistent visual identity design supported by digital platforms helps build a professional image, strengthen consumer trust, enhance brand recognition, and improve competitiveness. This study underscores the importance of visual identity and digital media as strategic and accessible tools for sustaining local creative enterprises in the digital era.
Implementation of a Web-Based Digital E-Catalog System Conceptual Design to Support Creative Entrepreneurship: A Case Study of Diorama Handmade Studio Maullana, Chandra; Soeryanto Soegoto, Eddy; Wahdiniwaty, Rahma; Sumitra, Irfan Dwiguna; Mukharil Bachtiar, Adam
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 development of MSMEs in the era of digital transformation requires a product communication model that is not only informative but also capable of integrating visual identity, system architecture, and creative entrepreneurship strategies in an integrated manner. This study aims to design and implement a conceptual design for a web- based digital E-Catalog system at Diorama Handmade Studio that functions not only as an information medium but also as a strategic instrument for strengthening visual identity and developing creative entrepreneurship. The method used is a case study with a qualitative approach through observation, in-depth interviews with brand owners, system documentation, and literature studies related to digital information media, UI/UX, and creative entrepreneurship. The system was developed using a Responsive Web Application (RWA) approach with a three-tier architecture (presentation layer, application layer, and data layer) and implemented at the Proof of Concept (PoC) stage. The results of the study show that the digitally designed E-Catalog is capable of representing the complexity of handmade product values through interactive zoom features, organized information structures, brand storytelling, and a dynamic database-based filtering system.
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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