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Journal of Technology Informatics and Engineering
ISSN 2961-9068 · Universitas Sains dan Teknologi Komputer · 76 artikel di indeks
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Artikel Jurnal
User-Centered Mobile Navigation: Evaluating Local Usability for Improved UX
Mobile navigation interfaces continue to be plagued by the key usability problem, particularly where widely accepted design traditions fail to address the specific local user population requirements and mental models. This research addresses this significant limitation by using a thorough…
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Optimization of Inclusive Education Through the Implementation of Artificial Intelligence: Opportunities and Challenges
Inclusive education is critical to ensuring equitable learning opportunities for all students, regardless of their abilities or backgrounds. This study aims to analyze the optimization of inclusive education by implementing artificial intelligence (AI), focusing on identifying the opportunities and…
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Optimization of Smart Home Energy Consumption Using Machine Learning-Based Load Forecasting
The growing demand for energy efficiency in smart homes necessitates accurate short-term load forecasting to enable adaptive scheduling and optimal resource allocation. Traditional forecasting models, such as Random Forest, have demonstrated limited capability in capturing sequential dependencies…
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Transforming Fraud Detection in Banking with Explainable AI : Enhancing Transparency and Trust
As financial fraud grows in complexity, banks are turning to artificial intelligence (AI) to identify and avert fraudulent actions. Nevertheless, the conventional black-box AI models often lack clarity, leading to issues related to trust, adherence to regulations, and customer assurance. This paper…
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The Architecture of Intellegent Transportation System based on Sensor Monitoring (Implementation in Jakarta Area)
Urban congestion and traffic inefficiencies pose significant challenges for developing cities such as Jakarta. Conventional traffic management systems often lack responsiveness and integration, leading to time delays, fuel wastage, and safety hazards. This study proposes the architecture of an…
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Decentralized AI on The Edge: Implementing Federated Learning for Predictive Maintenance in Industrial IoT Systems
The integration of Artificial Intelligence (AI) into Industrial Internet of Things (IIoT) systems has enhanced predictive maintenance strategies by enabling early detection of faults in machinery. However, centralized AI models often face challenges related to data privacy, latency, and…
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Evaluating Digital Transformation within Integration Limitations using Desk-Based Analytical Case Study
Digital transformation in developing regions frequently encounters challenges, including inadequate infrastructure, limited system integration, and uneven digital literacy. These constraints are especially significant in local government institutions where policy readiness and system…
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Smart Healthcare: Harnessing AI for Early prediction of Neurodegenerative disease
Neurodegenerative disorders such as Parkinson’s disease, Alzheimer’s disease, and Amyotrophic Lateral Sclerosis (ALS) are progressive conditions that result in the deterioration of neuronal function. Early diagnosis remains a significant challenge due to the subtle onset of symptoms and the lack of…
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Contextual Framework for Remote Intelligent Monitoring and Detection System for Prediction of Pregnancy Complications
Maternal health disorders can cause complications and harmful incidents in women during pregnancy. To minimize risks, this research developed a platform powered by a supervised machine learning model (SMLM) to support remote intelligent monitoring and prediction of pregnancy complications caused by…
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Virtual Reality in Adaptive Learning: Identifying Learning Styles and Integration in Educational Apps
The increasing demand for personalized education in digital environments has highlighted the limitations of traditional, static learning methods. This study addresses the challenge of accommodating diverse learning preferences and emotional responses by leveraging Virtual Reality (VR) to create…
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Predicting and Inspecting Food Contamination Using AI based Hyperspectral Imaging
Growing consumer demands and intricate supply networks are making it more difficult for the global food industry to maintain high standards of quality and ensure food safety. Conventional inspection techniques sometimes take a lot of time, cause damage, and are inaccurate enough to miss…
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Optimizing High-Frequency Antenna Design through Genetic Algorithm-Based Electromagnetic Simulation
The emergence of sixth-generation (6G) wireless networks demands broadband antennas capable of ultra-high data throughput and seamless global connectivity. This study presents a genetic-algorithm (GA) optimization framework to enhance antenna performance, focusing on patch dimensions, ground-plane…
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Zero-Shot Learning For Multilingual Document Classification In Low-Resource Languages
Document classification in low-resource languages remains a critical challenge due to the scarcity of annotated datasets, language-specific resources, and linguistic tools. This study investigates the effectiveness of zero-shot learning (ZSL) for multilingual document classification, with a…
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The Role of Social Media as a Micro-Ecosystem in Supporting Community-Based E-Learning Platforms: A Systematic Literature Review
This study explores the role of social media as a micro-ecosystem that supports community-based E-learning, adopting a Systematic Literature Review (SLR) approach guided by the PRISMA protocol. From 450 screened publications, 80 relevant studies were analysed using both qualitative thematic…
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Adaptive Control of Autonomous Mobile Robots Using Fuzzy Logic Based PID Optimization
Autonomous mobile robots require precise navigation and stability in dynamic environments, where traditional control methods often fail to balance accuracy, responsiveness, and robustness. This study proposes an adaptive fuzzy–PID control framework to optimize real-time trajectory tracking and…
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Adaptive Fuzzy Logic Integration for Optimizing Decision Support Systems under Data Uncertainty
Decision Support Systems (DSS) become inaccurate when used with imprecise, incomplete, or dynamically changing data. Fuzzy logic techniques based on conventional methodology may be strong at handling vagueness, but are unable to adapt their behavior to different data distributions on their own…
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A Hybrid Noise Reduction And Normalization Framework For Improving Multimodal Sensor Data Quality In Real-Time Systems
Multimodal sensor data, integrating signals such as RGB, LiDAR, and IMU, plays a pivotal role in enabling intelligent decision-making in real-time Internet of Things (IoT) systems. However, these data streams are inherently prone to complex noise patterns, cross-sensor inconsistencies, and scaling…
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Artificial Intelligence in Education Management: A Systematic Review of Decision Support Systems for Inclusive Education
This study examines the integration of artificial intelligence (AI) into education management systems, focusing on decision-support mechanisms for inclusive education. Through a systematic literature review of publications from 2019 to 2024, this research analyzes how AI technologies transform…
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Quantum-Inspired Optimization for High-Dimensional Data Classification in Healthcare Analytics
High-dimensional medical datasets pose a persistent challenge for artificial intelligence because traditional classification algorithms often incur escalating computational costs and reduced predictive accuracy. As healthcare systems generate increasingly complex clinical records, imaging outputs…
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3D Medical Image Reconstruction through Transformer-Based Neural Networks: A Comparative Study
Three-dimensional reconstruction of CT and MRI images remains a persistent challenge in medical imaging, where clinicians require high‐fidelity volumes that preserve subtle anatomical details while remaining computationally efficient. This study evaluates a transformer-based neural network against…