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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
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Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation
The journal covers all aspects of applied engineering, applied Science and information technology, that is: Engineering: Energy Mechanical Engineering Computing and Artificial Intelligence Applied Biosciences and Bioengineering Environmental and Sustainable Science and Technology Quantum Science and Technology Applied Physics Earth Sciences and Geography Civil Engineering Electrical, Electronics and Communications Engineering Robotics and Automation Marine Engineering Aerospace Science and Engineering Architecture Chemical & Process Structural, Geological & Mining Engineering Industrial Mechanical & Materials Science: Bioscience & Biotechnology Chemistry Food Technology Applied Biosciences and Bioengineering Environmental Health Science Mathematics Statistics Applied Physics Biology Pharmaceutical Science Information Technology: Artificial Intelligence Computer Science Computer Network Data Mining Web Language Programming E-Learning & Multimedia Information System Internet & Mobile Computing Database Data Warehouse Big Data Machine Learning Operating System Algorithm Computer Architecture Computer Security Embedded system Coud Computing Internet of Thing Robotics Computer Hardware Information System Geographical Information System Virtual Reality, Augmented Reality Multimedia Computer Vision Computer Graphics Pattern & Speech Recognition Image processing ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 659 Documents
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Localization-Safe Error Recovery: Ensuring Comprehension and Operability Across Languages and Scripts in High-Integrity User Journeys Harshit Sunilkumar Vora
International Journal of Engineering, Science and Information Technology Vol 6, No 2 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i2.1836

Abstract

Multi-factor authentication (MFA) has become a critical security mechanism for protecting digital services; however, the effectiveness of MFA depends heavily on the usability and reliability of account recovery processes. Existing evaluations of MFA recovery deployments report alarmingly high failure rates, with approximately one in two users unable to successfully complete recovery tasks under testing conditions even before localization factors are considered. This study investigates how localization influences recovery usability and argues that translation can systematically amplify recovery failures through predictable and classifiable mechanisms. Common issues include text expansion that truncates recovery instructions, grammatical reordering that displaces embedded identifiers, mixed bidirectional text that reverses verification codes, and typography-related height changes that obscure keyboard-focusable controls. These failures are not caused by linguistic inaccuracies but rather by correctly translated content interacting with interfaces that were not designed to accommodate the structural characteristics of target languages. To address this challenge, the study proposes a two-instrument engineering framework grounded in the principles of WCAG 2.2 accessibility standards. The first component is a recovery message schema that models required fields, interaction dependencies, and interface invariants across all recovery states. The second component is a localization hazard model that captures causal relationships among translation phenomena, structural interface failures, and resulting user harm. Together, these instruments establish a verifiable standard for localization-safe recovery design. A recovery workflow is considered localization-safe only when all schema properties are preserved, interaction invariants remain satisfied, and every identified hazard class within supported locales is mitigated through design and verification activities. The findings highlight that reliable recovery experiences cannot be achieved through linguistic review alone. Instead, localization safety must be embedded within release governance, verification architecture, accessibility testing, and localization management practices to ensure secure, inclusive, and globally deployable authentication systems?
Integration of Agricultural Automation, and Sustainable Tourism Businesses to Strengthen the Green Economy, and Achieve Food Self-Sufficiency in Wonosalam Village Agus Sukoco; Achmad Muchayan; Fetty Asmaniati; Nuryadi Nuryadi; Muhammad Ikhsan Setiawan; Che Zalina Zulkifli; Fazilat Kodirova
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1826

Abstract

The transition toward a green economy requires rural communities to adopt innovative strategies that integrate sustainable agriculture, technological advancement, and tourism-based economic development. Wonosalam Village in Jombang Regency, Indonesia, possesses considerable potential to support this transformation due to its fertile agroforestry landscapes, abundant biodiversity, agricultural productivity, and rapidly growing eco-tourism sector. This study examines the synergistic integration of agricultural automation and sustainable tourism as a strategic approach to improving food self-sufficiency, increasing rural income, and strengthening the local green economy. The research employs a mixed-methods approach, combining field surveys, participatory rural appraisal, direct observation, and stakeholder interviews involving farmers, tourism operators, local government officials, and community leaders. In addition, pilot implementations of small-scale automation technologies were conducted in horticultural and livestock production systems to assess their operational effectiveness and socio-economic impact. The findings indicate that the adoption of smart farming technologies, including automated irrigation systems, precision nutrient delivery, environmental monitoring sensors, and solar-powered post-harvest processing facilities, significantly improves resource efficiency, productivity, and product quality while reducing production costs and environmental pressures. Furthermore, the integration of agricultural activities with tourism experiences creates diversified income opportunities through farm-based recreation, agrotourism attractions, local product marketing, and educational programs focused on sustainable farming practices. The model also supports the principles of a circular economy by utilizing agricultural by-products as resources for tourism activities, organic fertilizer production, and environmental conservation initiatives. Community participation and stakeholder collaboration were identified as key factors for successful implementation. Overall, the study demonstrates that the integration of agricultural automation and sustainable tourism can enhance rural economic resilience, promote environmental sustainability, and contribute to the development of secure and sustainable food systems. The proposed model offers a practical and replicable framework for other rural regions seeking to achieve green economic growth and long-term community prosperity
Implementation of a Stunting Monitoring System for Toddlers Using the Analytical Hierarchy Process Method in Southeast Aceh Regency Padila Uvaira; Hafizh Al Kautsar Aidilof
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1814

Abstract

Stunting is one of the public health problems that remains a major challenge in Indonesia, including in Southeast Aceh Regency. Based on data from the Indonesian Nutritional Status Study (SSGI), the prevalence of stunting in Southeast Aceh Regency reached 34.1%, which is higher than the average prevalence in Aceh Province of 33.2%. The high rate of stunting indicates the need for more effective monitoring and handling efforts to support the growth and development of toddlers. Currently, the process of monitoring stunting in community health centers is still carried out manually, causing delays in data processing, calculation errors, and a lack of objectivity in assessing the nutritional status of toddlers. Manual recording also makes it difficult for health workers to monitor toddler development accurately and periodically. Therefore, an effective and computerized monitoring system is needed to support health services in determining stunting status more efficiently. This study aims to implement a web-based stunting monitoring system using the Analytical Hierarchy Process (AHP) method to assist health workers in determining the stunting status of toddlers more quickly, accurately, and systematically. The AHP method is applied by assigning weights to several assessment criteria, namely age, weight, height, and nutritional status. Through the weighting and calculation process, the system generates a final score used as the basis for determining whether a toddler is categorized as normal or stunted. The results of this study indicate that the application of the AHP method can support decision-making processes more objectively compared to manual methods. In addition, the developed system provides a toddler growth chart feature that helps health workers and parents monitor child development regularly. Therefore, this system is expected to improve the effectiveness and efficiency of stunting monitoring in Southeast Aceh Regency and support government efforts to reduce the prevalence of stunting.
Autonomous Fish Feeding Integrated System for Food Self-Sufficiency and Aquatourism Development in Malang City Taufiqur Rokhman; Aeri Sujatmiko; Hj. Lis Setyowati; M Husen Hutagalung; Muhammad Ikhsan Setiawan; Che Zalina Zulkifli; Zulfiya Khabirova; Fazilat Kodirova
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1832

Abstract

This article examines the integration of autonomous fish-feeding systems with salt production and fish processing technologies as an innovative strategy to enhance food self-sufficiency, strengthen rural economies, and promote aquatourism development in Malang Regency, Indonesia. The region possesses significant potential in aquaculture, fisheries, and coastal resource utilization; however, productivity remains constrained by inefficient feeding practices, limited technological adoption, outdated processing methods, and infrastructure disparities. These challenges reduce production efficiency, increase operational costs, and limit the competitiveness of local fishery products in broader markets. The study employs a qualitative and participatory approach based on stakeholder engagement, field observations, focus group discussions, and technological gap analyses involving fish farmers, salt producers, tourism operators, local governments, and community organizations. The research develops an integrated innovation model that combines autonomous fish-feeding systems, smart aquaculture management, sustainable salt production, and value-added fish processing technologies within a unified economic ecosystem. The proposed model is designed to improve production efficiency while creating new tourism attractions centered on fisheries, coastal culture, and environmental education. The findings indicate that the adoption of automated feeding technologies can significantly reduce feed waste, lower operational costs, improve fish growth performance, and enhance overall aquaculture productivity. In addition, integrating fish processing and salt production activities with aquatourism creates diversified income sources, increases employment opportunities, and supports local entrepreneurship. The model also contributes to environmental sustainability by promoting efficient resource utilization and reducing production-related waste. The study concludes that the integration of autonomous aquaculture technologies with fisheries-based tourism represents not only a technological advancement but also a strategic pathway for economic transformation in coastal and rural regions. Furthermore, the proposed framework offers a scalable and replicable model for achieving sustainable food systems, community resilience, and inclusive regional development in Indonesia and other developing countries.
The Role of MRP Systems in Large-Scale LNG Pipe Spool and Modular Fabrication: Integration with EPC Project Delivery Sachin Pal Singh
International Journal of Engineering, Science and Information Technology Vol 6, No 2 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i2.1847

Abstract

Large-scale liquefied natural gas (LNG) projects represent some of the most logistically complex undertakings in industrial engineering, requiring the coordinated fabrication of tens of thousands of pipe spools across geographically distributed facilities while maintaining strict cost, schedule, quality, and regulatory requirements. Despite advances in digital manufacturing, limited research has examined how integrated material requirements planning (MRP) systems support synchronized fabrication at mega-project scale. This paper investigates the implementation of an integrated MRP framework at Fabrication Manufacturing facilities supporting LNG projects, where approximately 100,000 pipe spools were fabricated across six production facilities using a centralized planning and distributed execution architecture. The proposed framework aligns with Advanced Work Packaging (AWP) principles recommended by the Construction Industry Institute (CII), ISA-95 enterprise-control integration standards, and ASME/API engineering compliance requirements to enhance coordination between planning, procurement, inventory management, and shop-floor execution. The implementation introduces a bidirectional integration model between the MRP system and the Manufacturing Execution System (MES), enabling real-time synchronization of production schedules, material availability, fabrication status, and inventory data across all participating facilities. Furthermore, a centralized pre-buy material distribution strategy minimizes procurement uncertainty and improves supply chain responsiveness. Empirical results demonstrate an 18–25% reduction in procurement lead time, a 20–30% increase in fabrication productivity through AWP-aligned sequencing, and improved schedule reliability across multi-site operations. The integrated digital planning architecture also enhanced resource utilization, reduced production bottlenecks, and strengthened cross-facility coordination. These findings establish integrated MRP implementation as a critical enabler of efficient mega-scale LNG fabrication delivery and provide a practical, scalable, and replicable framework for engineering, procurement, and construction (EPC) contractors managing highly complex industrial projects.
Enhancing the Income of Mie Lidi Microenterprises in the Underdeveloped Village of Banjarsari, Demak Regency Through the Implementation of Solar-Powered Portable Automatic IoT Blower Technology Sunu Arsy Pratomo; Purwanto Purwanto; Fatchur Roehman; Muhammad Ikhsan Setiawan; Che Zalina Zulkifli; Zulfiya Khabirova
International Journal of Engineering, Science and Information Technology Vol 6, No 2 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i2.1840

Abstract

This study investigates the integration of solar energy technologies to improve operational efficiency, reduce production costs, and enhance income generation among micro and small enterprises in rural Indonesia. The research focuses on the mie lidi processing sector in Banjarsari Village, Demak Regency, where traditional drying practices remain highly dependent on weather conditions, resulting in inconsistent production quality and limited productivity. To address these challenges, the study introduces a solar-powered Portable Automatic Internet of Things (IoT) Blower designed to automate and optimize the drying process while utilizing renewable energy as the primary power source. The proposed system incorporates two 550-watt monocrystalline solar panels integrated with IoT-based monitoring and automated airflow control mechanisms. Performance evaluation demonstrates that the solar energy system generates an average of 6.69 kilowatt-hours (kWh) of electricity per day, equivalent to approximately 187.2 kWh per month. Meanwhile, the blower requires only 0.864 kWh of energy per day, representing 12.9% of total energy production, thereby creating a substantial energy surplus that supports long-term operational sustainability. The implementation of the system produces estimated monthly electricity cost savings of IDR 270,447.24, significantly reducing operational expenditures for local enterprises. Beyond economic benefits, the automated drying technology enhances production consistency by eliminating dependence on fluctuating weather conditions and reducing processing delays. The integration of renewable energy and smart automation also contributes to environmental sustainability through lower carbon emissions and reduced reliance on fossil-fuel-based electricity. The findings indicate that solar-integrated IoT drying systems offer a practical, scalable, and environmentally friendly solution for strengthening rural entrepreneurship, increasing productivity, and supporting sustainable economic development. Furthermore, the proposed model provides a replicable framework that can be adopted by other rural communities with similar climatic and socio-economic conditions to promote energy independence and resilient local industries
Token-Aware API Design Patterns for Model Context Protocol Integration in Enterprise Distributed Systems Nikhil Bharadwaj Ramashasthri
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1854

Abstract

Autonomous software agents operating through the Model Context Protocol (MCP) reveal a fundamental architectural mismatch between conventional REST API design and the finite context windows of Large Language Model (LLM) inference engines. Enterprise backend services originally optimized for browser-based applications typically return payloads enriched with deeply nested relational structures, verbose infrastructure metadata, and redundant serialization artifacts. While acceptable for human-operated interfaces, these responses unnecessarily consume LLM context capacity when delivered through MCP servers, increasing inference costs, reducing reasoning efficiency, and limiting the number of actionable interactions that autonomous agents can perform. This article investigates serialization-boundary optimization as a critical architectural concern for MCP-native systems and proposes four composable backend design patterns: Semantic Envelope, infrastructure metadata pruning, dynamic token-aware pagination, and GraphQL interface projections. Together, these patterns restructure API responses to maximize semantic density while minimizing token consumption without modifying underlying domain models or persistence layers. The implementation is demonstrated in enterprise environments built on Spring Boot and Hibernate, illustrating seamless integration with existing software architectures. Experimental evaluation using production entity structures from a peer-to-peer car-sharing marketplace processing millions of vehicle transactions annually shows token reductions ranging from 34% to 86% across the proposed patterns, a 40% decrease in API pagination cycles, and a 97% reduction in response latency through a two-tier semantic caching strategy deployed over an 11.5-million-row persistence layer sustaining approximately 48,900 read operations per minute. These findings demonstrate that context-aware serialization significantly improves LLM agent efficiency while preserving enterprise scalability, interoperability, and maintainability. The proposed framework provides a practical engineering vocabulary and reference architecture for designing token-efficient, MCP-native backend systems capable of supporting the next generation of autonomous AI agents in large-scale enterprise environments.
Deep Learning Methods for Pneumonia Detection Using ConvNeXt Architecture Akhmad Irsyad; Muhammad Bambang Firdaus; Gubtha Mahendra Putra; Putut Pamilih Widagdo; Hario Jati Setiady; Muhammad Fawaz Saputra; Muhammad Abdillah Rahmat
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1797

Abstract

Pneumonia remains a major respiratory infection with high mortality rates, especially in regions with limited access to medical specialists. Early and accurate diagnosis plays a critical role in reducing fatal outcomes and improving patient management. Chest X ray imaging is widely used as a primary diagnostic modality, yet interpretation relies heavily on experienced radiologists, whose availability is often insufficient to meet clinical demand. This condition motivates the development of automated pneumonia detection systems based on artificial intelligence. This study investigates the application of deep learning for pneumonia classification using chest X ray images, with a focus on the ConvNeXt architecture. ConvNeXt represents a modern neural network design that integrates structural advantages from Vision Transformers with the efficiency of traditional Convolutional Neural Networks, enabling strong feature extraction while maintaining computational efficiency. The research evaluates multiple ConvNeXt variants, including Tiny, Small, Base, and Large, to analyze the relationship between model complexity and classification performance. ResNet50 is employed as a baseline model to provide a fair comparative assessment against a widely used convolutional architecture. Model evaluation uses accuracy, precision, recall, and F measure to ensure balanced measurement across different classification outcomes and class distributions. Experimental results indicate that ConvNeXt Tiny achieves the highest overall performance, reaching an accuracy of 97.69 percent while using a relatively low number of parameters. This outcome highlights the efficiency of lightweight architectures for medical image analysis tasks. The findings demonstrate that ConvNeXt Tiny delivers strong discriminative capability with reduced computational requirements, making it suitable for deployment in resource constrained clinical environments. This study contributes evidence supporting the effectiveness of modern deep learning architectures for automated pneumonia detection and provides insight into model selection for practical medical imaging applications.
Structural Equation Modeling Analysis of Critical, Creative, and Metacognitive Thinking Skills as Predictors of Reflective Thinking in Science Problem Solving Diki Rukmana; Andi Suhandi; Achmad Samsudin
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1007

Abstract

This study aims to model the relationships between critical, creative, and metacognitive thinking skills in shaping reflective thinking abilities among prospective science teachers, particularly within the context of solving complex science problems. A quantitative research approach was employed using Structural Equation Modeling (SEM), with data analysis conducted through SmartPLS software. The sample consisted of 162 students enrolled in science education courses during the odd semester of the 2024/2025 academic year. Data were collected using a standardized questionnaire that had undergone systematic content validity and reliability testing to ensure measurement accuracy and consistency. The measurement model analysis demonstrated that all indicators satisfied established validity and reliability criteria, with factor loading values exceeding 0.70 and Average Variance Extracted (AVE) values above 0.50. Furthermore, the structural model analysis revealed that critical thinking skills exerted the strongest positive and significant influence on reflective thinking abilities (? = 0.401; p 0.001), followed by metacognitive skills (? = 0.337; p 0.001) and creative thinking skills (? = 0.178; p 0.05). The coefficient of determination (R² = 0.716) indicates that the proposed model explains 71.6% of the variance in reflective thinking ability, demonstrating substantial explanatory power. These findings confirm that reflective thinking develops through the synergistic interaction of multiple higher-order thinking competencies rather than through isolated cognitive processes. Critical thinking supports systematic evaluation of evidence and reasoning, metacognitive skills facilitate awareness and regulation of cognitive strategies, while creative thinking encourages flexible exploration of alternative solutions. This study contributes to the advancement of theoretical frameworks in science teacher education and provides practical implications for designing instructional strategies, problem-based learning activities, reflective assessments, and teacher preparation programs that systematically integrate critical, creative, and metacognitive competencies to strengthen prospective science teachers’ reflective thinking and professional decision-making capabilities
Integrated Smart Agriculture, and Sustainable Tourism Model for Advancing Green Economy And Food Self-Sufficiency In Wonosalam Village Nuryadi Nuryadi; Ony Thoyib Hadiwijaya; Koesriwulandari Koesriwulandari; Muhammad Ikhsan Setiawan; Che Zalina Zulkifli; Zulfiya Khabirova
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1855

Abstract

This study explores the integration of ecotourism and smart agriculture as a strategic approach to strengthening the green economy and achieving local food sovereignty in Wonosalam Village, Jombang Regency, Indonesia. The research develops and validates a solar-powered smart durian farming system that integrates renewable energy, precision irrigation, organic fertilization, environmental sensing, Internet of Things (IoT) technology, and artificial intelligence (AI)-based decision support. The proposed system continuously monitors key environmental parameters, including soil moisture, temperature, humidity, solar radiation, and nutrient conditions, enabling real-time recommendations for irrigation, fertilization, and crop management. A mixed-methods approach combining field observations, stakeholder engagement, system validation, and performance evaluation was employed to assess the technological, environmental, and socio-economic impacts of the integrated model. The findings demonstrate that the implementation of intelligent farming technologies significantly improves durian productivity, optimizes water and energy utilization, reduces dependence on chemical fertilizers through organic nutrient management, and enhances farm operational efficiency. Simultaneously, the integration of interactive ecotourism activities, environmental education, and digital monitoring platforms creates additional income opportunities for local communities while increasing public awareness of sustainable agriculture and biodiversity conservation. The proposed model establishes a circular rural economy by connecting agricultural production, renewable energy utilization, environmental stewardship, tourism services, and local entrepreneurship within a single integrated ecosystem. Furthermore, the system strengthens community participation, promotes technology adoption among farmers, and enhances resilience against climate variability. The study concludes that combining smart agriculture with ecotourism provides a scalable and replicable rural development framework capable of supporting national green economy strategies, decentralized food sovereignty initiatives, sustainable tourism development, and long-term environmental sustainability in agricultural regions

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