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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
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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 775 Documents
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End-to-End Automation for Device Lifecycle Management, Compliance, and Operational Resilience Miteshkumar Jagdishbhai Patel
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.v6i2.2024

Abstract

Manual configuration workflows in enterprise networks can cause configuration drift, compliance failures, and change-related outages because operational consistency depends heavily on individual execution across large and continuously changing device populations. This paper examines an end-to-end network configuration automation framework based on Infrastructure as Code (IaC) principles to establish a controlled lifecycle for configuration provisioning, validation, deployment, monitoring, remediation, and governance. The framework integrates zero-touch provisioning, continuous compliance validation, risk-governed change management, staged deployment, rollback, and self-validating governance into an interdependent operational process in which each lifecycle phase provides the configuration state and evidence required by subsequent phases. The analysis indicates that deterministic configuration, continuous drift detection, pre-change validation, controlled execution, tested rollback, and automated governance can shift configuration consistency and compliance from periodic administrative activities toward continuously maintained operational properties. The framework also identifies risks associated with extensive automation, including engineering and maintenance requirements, centralized blast radius, incorrect or overly broad remediation, and organizational dependence on controlled automation workflows. These risks are addressed through explicit safeguards, including idempotent reconciliation, validation gates, staged execution, bounded remediation authority, rollback mechanisms, and independent verification of automation health. The resulting framework provides a structured approach for scalable, auditable, and resilient enterprise network operations by integrating configuration management, operational assurance, change control, and governance within a unified lifecycle. The framework further establishes a basis for evaluating automation reliability across heterogeneous and multi-vendor environments, particularly through standardized verification of idempotency, failure containment, and automation blast radius. Such an evaluation can support the safer deployment of automated network operations at increasing scale
Package-Centric Fulfillment Orchestration in Live Commerce: An Event-Driven Microservices Architecture Hima Bindu Yanala
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.v6i1.2060

Abstract

Live commerce fulfilment is characterized by simultaneous surges in orders, rapid conversion from viewer engagement to purchase, and transactions involving multiple sellers. Conventional order-centric fulfilment architectures may produce partially completed orders when inventory, payment, carrier, or notification processes fail independently across sellers and supporting services. The study proposes a package-centric fulfilment architecture in which the package aggregate represents a single seller-to-buyer shipment unit and functions as the consistency boundary and failure-isolation scope. The architecture is implemented as six bounded microservices that communicate through domain events using Apache Kafka, with topic partitioning by package identifier to preserve per-package event ordering without synchronous inter-service coupling. The outbox pattern maintains consistency between local service state and published events, while idempotent consumer registries prevent duplicate state changes under at-least-once event delivery. A choreography-based saga defines bounded compensating paths for four representative failure scenarios: inventory exhaustion, carrier rejection, payment failure, and notification delivery loss. Scenario-based evaluation assesses each scenario for compensation scope, state-preservation guarantee, and idempotency safety under concurrent and asynchronous operating conditions. The evaluation shows that all four failure scenarios have explicit compensating paths and that compensation remains confined to the affected package rather than propagating across unrelated packages or sellers. Local state transitions remain protected against duplicate event processing, while package-level consistency is preserved during compensation. These results establish a structural mechanism for isolating partial-fulfilment failures while maintaining a coherent package state across distributed services. The proposed architecture provides a foundation for subsequent empirical assessment of recovery performance, event-processing latency, throughput, and operational reliability in live commerce fulfilment environments
Revisiting Attention Modules for Still-Image Human Action Recognition: A Multi-Seed Evaluation on Stanford-40 Rokhmat Febrianto; Ayomi Sasmito
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.1989

Abstract

Attention modules such as Squeeze-and-Excitation are often reported to improve convolutional neural networks for human action recognition in still images. Most of these reports, however, rely on a single training run, and published scores on the same benchmark are frequently obtained under different train–test splits. This study examines whether the reported benefit remains under a controlled evaluation. Four modules, namely Squeeze-and-Excitation (SE), the Convolutional Block Attention Module (CBAM), Efficient Channel Attention (ECA), and the parameter-free SimAM, were inserted into ResNet-34 at four positions and trained on the Stanford-40 Actions dataset under its official split with one fixed training recipe, giving 44 trained models. The four all-stage configurations were repeated with six random seeds and compared using a paired Wilcoxon signed-rank test and an exact McNemar test. Replacing the official split with a random 80/20 split increased test accuracy by 3.19 to 4.52 percentage points across four backbones, a larger change than any module produced. Across six seeds, SE changed macro-F1 by +0.06 points, within the seed-to-seed range of the unmodified baseline, whereas ECA and SimAM reduced it by 1.56 and 0.74 points. No module improved on the baseline by a statistically supported margin, yet every module increased single-image CPU latency by 4.3% to 18.3% while adding less than 0.02% in floating-point operations. The findings show that the evaluation protocol and run-to-run variance affect reported scores more than the modules themselves, and a reporting checklist is proposed for future evaluations of such modules
Knowledge, Attitude, and Practice of Breast Self-Examination among Women of Reproductive Age Reghita Claudia Malau; Jumadi Jumadi; Cantika Viona Adytia Hutagalung; Widya Yanti Sihotang
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.1999

Abstract

Breast cancer remains a major health problem among women, and early detection plays an important role in increasing the opportunity for timely diagnosis and appropriate treatment. Breast self-examination (BSE) is a simple, low-cost, and accessible method that can be performed routinely at home to identify abnormal changes in the breast at an early stage. This study aimed to examine the relationship between knowledge, attitudes, and BSE practices among women of childbearing age in Sei Putih Barat Village, Medan Petisah District. An analytical survey using a cross-sectional design was conducted among 110 women of childbearing age who were selected through purposive sampling. Data was collected using a structured questionnaire covering respondents’ knowledge, attitudes, and BSE practices. The collected data were analyzed using bivariate analysis with the chi-square test and odds ratios (ORs) to determine the strength of associations between variables. The results showed that most respondents had inadequate knowledge (75.5%), negative attitudes (83.6%), and inadequate BSE practices (66.36%). Knowledge was significantly associated with BSE practice (p = 0.021), with respondents who had adequate knowledge being 3.43 times more likely to perform BSE adequately. Attitude demonstrated a stronger association with BSE practice (p 0.001), with respondents who had positive attitudes being 14.53 times more likely to perform BSE adequately. These findings indicate that both knowledge and attitudes are significantly associated with BSE practices among women of childbearing age. Therefore, interventions aimed at improving BSE practices should integrate health education, practical guidance, and strategies designed to strengthen positive attitudes and perceptions toward early breast cancer detection and prevention
Integrated Transportation and Queueing System Model for Optimizing the Logistics Efficiency of Freight-Forwarding Services at Nabire Port Agung Nugroho
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.2015

Abstract

Nabire Port is the main logistics node of Central Papua Province, yet its service performance has rarely been examined from a queueing perspective using operational data recorded at the level of individual arrivals. This study analyses ship services and freight-forwarding truck services at Nabire Port as two separately observed subsystems and combines their subsystem-level results into a constructed logistics-time indicator, not a verified tandem queue. The novelty of the study lies in its empirical comparison of classical queueing benchmarks with observed timestamps in a multi-cargo regional port, together with an explicit assessment of when those benchmarks are and are not applicable. Primary data comprising 60 ship arrivals (July-September 2026) and 60 forwarding-truck arrivals (July 2026) were analysed using M/M/1 and M/M/c models. Distributional assumptions were tested using the Kolmogorov-Smirnov test, and theoretical results were compared with observed waiting times and, for the single-server case, the Kingman approximation. The ship system was stable, with a utilisation of 0.391, a theoretical waiting time of 9.15 hours, and a time in system of 23.40 hours, whereas the observed mean waiting time was 1.33 hours. The single-server truck model gave a utilisation of 0.907 and a theoretical waiting time of 26.34 hours, far above the observed mean of 0.49 hours, because up to three trucks were served simultaneously. In the M/M/c scenario with two service channels, the theoretical truck waiting time fell to 0.70 hours and the combined ship-truck indicator to 26.81 hours, compared with 52.45 hours with one channel. The Kolmogorov-Smirnov tests rejected the exponential assumptions for all inter-arrival and service times; therefore, the M/M results are interpreted as theoretical baselines and model-based scenario indications, not as validated predictions or as an economically optimal capacity, since no cost data were analysed
Explainable Environmental Decision Support System for Drought Monitoring with Decision-Tree Knowledge, Fuzzy Reasoning, and Independent SMAP Evidence in Indonesia Muhammad Irfan; Ditdit Nugeraha Utama
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.1937

Abstract

The increasing need for explainable environmental decision support requires drought monitoring systems to move beyond categorical classification toward traceable and operationally meaningful recommendations. This study proposes an Explainable Environmental Decision Support System (EEDSS) that integrates a Decision Tree, fuzzy reasoning, operational decision mapping, and independent SMAP soil-moisture evidence for drought monitoring in Indonesia. NASA POWER meteorological observations from 470 spatial locations covering 2020-2024 were used, with SPEI-3 serving as the reference for nine dry-to-wet environmental states. A Decision Tree was developed using 2020-2023 data and evaluated on an independent 2024 temporal test set. The selected balanced Decision Tree achieved an accuracy of 0.721, balanced accuracy of 0.704, and Macro-F1 of 0.681, indicating moderate classification performance while providing an interpretable structure for extracting 110 meteorological rules. These rules were transformed through fuzzy reasoning into continuous environmental evidence and five operational categories: NORMAL, WATCH, URGENT, WET WATCH, and URGENT WET. All 27,723 observations received an operational recommendation. Independent SMAP Level-4 observations provided valid SSM and RZSM evidence for 98.72% of the observations. SSM demonstrated the expected dry-to-normal-to-wet directional consistency, whereas RZSM did not. Both variables showed statistically significant distributional differences across the nine environmental states based on the Kruskal-Wallis test (p 0.05). Overall, the findings indicate that EEDSS provides a transparent decision-support pipeline with partial independent environmental consistency, particularly at the surface soil-moisture level. The system is therefore positioned as an explainable environmental decision-support framework, rather than solely as a high-accuracy drought classification model
Autonomous Test Case Generation from API Specifications Using AI: A Hybrid LLM and Reinforcement Learning Framework Onkar Khadke
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.v6i1.2032

Abstract

The rapid growth of REST API surfaces in microservice architectures has increased the difficulty of achieving meaningful specification-level test coverage through manually authored test suites. This study presents a hybrid autonomous test-generation framework that improves REST API testing by leveraging the dependencies and semantic information encoded in OpenAPI specifications. The framework integrates four components: a Spec-Semantic Graph that represents endpoint dependencies as a weighted directed graph; a Contextual Boundary Inference Engine that uses few-shot large language model prompting to infer semantic boundary conditions from OpenAPI descriptions; a Coverage-Aware Reinforcement Learning Test Scheduler that prioritizes test execution using a multidimensional coverage state vector; and a Differential Oracle Synthesis mechanism that constructs pass/fail verdicts without manually authored expected-output specifications. The framework was evaluated using three open-source REST APIs representing different levels of specification completeness, which were compared with large language model and search-based testing baselines. The evaluation examined endpoint coverage, oracle accuracy, and continuous integration overhead across the tested APIs. Results show that the proposed framework achieves higher endpoint coverage than the individual baselines and reduces oracle false-positive rates by combining specification semantics with adaptive test prioritization and automated differential validation. The framework also introduces a one-time continuous integration overhead for constructing semantic representations and learned test states, which can be amortized across subsequent specification versions. These findings indicate that specification semantics, contextual boundary inference, adaptive scheduling, and automated oracle synthesis can be integrated into a unified autonomous testing process. The framework, therefore, provides a specification-native quality assurance pipeline that derives test intelligence directly from OpenAPI specifications while reducing dependence on manually authored test annotations
Architecting Scalable Telemetry Ingestion Fabrics Venkata Velavarthipati
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.v6i2.2064

Abstract

This paper proposes a four-tier telemetry ingestion architecture that integrates adaptive sampling, backpressure-aware streaming, schema-evolution-tolerant storage, and independent telemetry consumers into a unified processing fabric. The study aims to characterize the architectural trade-offs associated with telemetry reduction, anomaly preservation, buffering, recovery, and schema compatibility as observability workloads change. The architecture is evaluated through a controlled synthetic simulation rather than production measurements. Ten independent random seeds are executed under normal, anomaly, backpressure, and combined anomaly/backpressure regimes. Fixed-rate, tail-based, and confidence-gated adaptive sampling strategies are compared using telemetry volume reduction and anomaly coverage. At the same time, peak buffering, data loss, and recovery behavior are examined under constrained downstream processing. A separate schema-evolution experiment evaluates tolerance to the addition of telemetry fields without requiring modifications to existing downstream consumers. The simulation results indicate that adaptive sampling can reduce telemetry volume while preserving a substantial proportion of anomalous observations. However, the degree of reduction and preservation varies across sampling strategies and operating conditions. Backpressure scenarios demonstrate how constrained downstream processing affects buffer accumulation, data loss, and recovery behavior, highlighting the importance of explicit streaming control. The schema-evolution experiment indicates that additive changes to telemetry structures can be accommodated without disrupting independent consumers when storage and interface compatibility are decoupled from consumer processing logic. These results provide comparative evidence of architectural behavior under controlled conditions rather than production performance measurements. The study concludes that separating sampling, streaming control, storage compatibility, and consumer processing provides a structured architectural basis for managing telemetry ingestion under variable observability demands while making key trade-offs explicit for subsequent empirical validation
Implementation of a Design System as Standardized Development Guidelines for Consistent iOS User Interface Development: A Case Study of the Jasa Perantara Application Rahmannur Rizki Syahputra; Maria Seraphina Astriani
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.1893

Abstract

The increasing complexity of mobile application development creates challenges in maintaining consistent user interface (UI) implementation, particularly when design specifications are translated into software code by different developers. This study aims to implement a Design System as standardized development guidelines for the iOS version of the Jasa Perantara mobile application using SwiftUI. The study employed an implementation-oriented qualitative case study approach consisting of four stages: existing design analysis, Design System development, Design System implementation, and implementation verification. The analysis examined eight representative application screens and identified recurring UI elements requiring standardization. The developed Design System incorporated five reusable UI components, eleven standardized typography styles based on Apple’s Human Interface Guidelines, five color token categories, and three button variants. The Design System was subsequently integrated into the Jasa Perantara iOS application, with four application screens migrated to standardized components and three iOS developers involved in the implementation. Verification results indicated improved consistency between design specifications and software implementation, along with a reduction of approximately 30–40% in UI-related testing and bug-fixing activities. The findings demonstrate that a Design System can function not only as a reusable UI component library but also as a practical development guideline and single source of truth that reduces implementation ambiguity, supports collaboration between designers and developers, and improves software maintainability. The study concludes that integrating a Design System directly into a SwiftUI-based production application provides an effective approach for standardizing iOS interface development, enhancing consistency, reducing repetitive implementation effort, supporting sustainable application maintenance, and strengthening development coordination across teams and future application iterations
Scalable Gemini-Based Code Review System: An Asynchronous Microservices Architecture for Learning Analytics Didin Wahyudin; Naufal Nadhif Rabbani Iskandar
International Journal of Engineering, Science and Information Technology Vol 6, No 4 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i4.1971

Abstract

Manual inspection of students' GitHub commit histories to assess their programming activity presents significant scalability challenges when handling numerous repositories across a semester. This research developed and evaluated an AI-based commit analysis system that uses the Gemini language model to generate natural-language summaries of student programming activity, intended to support lecturers' review of GitHub-based coursework. The system was implemented using a prototyping methodology with an asynchronous, containerized architecture comprising a Vue.js front-end, a Laravel back-end, a PostgreSQL database, and a Redis-based job queue deployed in separate Docker containers. To keep the user-facing application responsive, AI analysis is processed asynchronously through a provider-abstraction layer accessing Gemini 2.5 Flash-Lite via OpenRouter, decoupling user interactions from computationally intensive model inference. System performance was evaluated using Apache JMeter on a 2-vCPU, 4-GB-RAM server, following the Performance Efficiency and Reliability characteristics of ISO/IEC 25010:2023. The back-end demonstrated a 0% error rate across 4,625 GitHub Feature requests. However, mean response time increased from 346.0 ms (10 users) to 6,743.8 ms (100 users), with throughput plateauing beyond 25 concurrent users, indicating a practical capacity threshold of 25–50 concurrent users. The AI Feedback path achieved a 100% success rate with a synchronous request-dispatch latency of 2.5–3.8 s across 90 requests; these are user-facing dispatch latencies and exclude LLM inference time. These results demonstrate the technical feasibility of the proposed asynchronous architecture for AI-assisted commit analysis at a moderate classroom scale; they do not constitute an evaluation of the accuracy, pedagogical usefulness, or learning-outcome impact of the generated feedback, which remain directions for future work. The primary limitation observed is performance degradation under high concurrency, which will require caching, database connection pooling, and vertical scaling for broader institutional deployment

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