cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Dahlan Abdullah
Contact Email
dahlan@unimal.ac.id
Phone
+62811672332
Journal Mail Official
ijestyjournal@gmail.com
Editorial Address
Jl. Tgk. Chik Ditiro, Lancang Garam, Lhokseumawe, Aceh - Indonesia, 24351
Location
Kota lhokseumawe,
Aceh
INDONESIA
International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
Core Subject : Science, Education, Social, Engineering,
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 775 Documents
 71   72   73   74   75 
Causal Geospatial Intelligence Framework for Identifying Environmental Drivers of Landslide Risk in Mountainous Regions Hayati Hehamahua; Arlis Dewi Kuraesin
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.v6i4.1917

Abstract

Landslide susceptibility models can effectively predict areas prone to landslides but generally provide limited evidence on whether specific environmental exposures causally influence landslide occurrence. This research proposes an integrated causal-geospatial framework combining predictive modeling with causal effect estimation and spatial heterogeneity analysis for landslide occurrence in Desa Wih Pase, Bener Meriah, Indonesia. An analytical dataset comprising 18,450 30 m × 30 m grid cells from observations in 2025 was analyzed using Random Forest and Logistic Regression for occurrence probability modeling, followed by Causal Forest to derive average treatment effect estimates together with grid-level Conditional Average Treatment Effects (CATE). The Random Forest model reached a discrimination performance of 0.91 in AUC-ROC, exceeding the 0.79 achieved by the Logistic Regression baseline, demonstrating stronger predictive discrimination under the imbalanced landslide dataset. Causal analysis estimated a positive effect of cumulative rainfall, with a 100 mm increase associated with a 0.142 increase in landslide occurrence probability (95% CI: 0.089–0.195). A 10° increase in slope produced an estimated effect of 0.218 (95% CI: 0.161–0.275). Spatial CATE analysis revealed substantial heterogeneity, with rainfall effects ranging from ?0.039 to 0.302 and slope effects from ?0.024 to 0.490 across valid 30 m grid cells. Sensitivity analyses showed that the positive causal effects remained stable across alternative confounder sets, rainfall accumulation windows, and spatial resolutions. The framework distinguishes predictive susceptibility from causal environmental effects and provides a basis for spatially targeted landslide risk reduction and environmental engineering interventions
Trustworthy Measurement Infrastructure as an Enabler of Data-Driven Innovation: A Conceptual Framework and Design Science Evaluation Manish Singh
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.v6i3.2034

Abstract

Data-driven innovation increasingly depends on controlled online experimentation to determine whether proposed changes improve organizational outcomes before broad deployment. However, the reliability of the measurement infrastructure that supports evidence-based experimentation remains insufficiently addressed. This article proposes the Trust-Aware Experiment Measurement Framework (TAEMF), a conceptual framework for governing measurement reliability in organizational experimentation. The framework integrates four measurement layers covering exposure capture, behavioral event integration, identity attribution, and curated metric modeling with a five-stage validation protocol and a formally defined trust-state model that determines whether experiment results are sufficiently reliable for promotion to decision systems. The framework is developed and evaluated using a Design Science Research methodology combined with discrete-event simulation. The simulation models 200 concurrent experiments over 60 days under five infrastructure degradation conditions and compares TAEMF with conventional and partial-validation baselines. Results show that TAEMF detects 81–97% of measurement failures across the tested conditions, compared with 5–88% for the conventional baseline and 31–91% for the partial-validation baseline. TAEMF also reduces the rate of invalid experiment results from 0.19–0.61 to 0.02–0.04. An ablation analysis demonstrates that each validation stage contributes to the framework's overall failure-detection capability, indicating that measurement reliability depends on coordinated validation rather than isolated controls. The findings establish the trustworthiness of measurement infrastructure as an important dimension of organizational experimentation capability. TAEMF provides a structured governance mechanism for assessing measurement reliability before experimental evidence is used to support organizational decisions and offers a systematic basis for strengthening the evidentiary foundation of data-driven innovation
Customer Engagement, E-Commerce Personalization, Maintenance Workflow Automation, Post-Purchase Experience, Recommendation Systems Ranjith Kontham
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.v6i2.2066

Abstract

Post-purchase interactions remain an important but comparatively underdeveloped component of digital commerce platform design. This study aims to develop an architectural and experience-design perspective for transforming the product ownership lifecycle into a continuous digital engagement environment. The study adopts a conceptual synthesis approach that integrates design considerations from product ownership management, maintenance workflows, contextual recommendation systems, platform performance, and scalable service architecture. The analysis examines how these elements can be structured as an integrated post-purchase platform rather than as isolated customer-service functions. The results identify ownership certainty as a central mechanism for improving recommendation relevance, as verified product relationships provide a reliable basis for compatibility-aware suggestions for products and services. Maintenance workflows provide recurring interaction points while generating structured behavioral signals that can support contextual personalization throughout the ownership lifecycle. At the architectural level, progressive rendering, mobile-oriented optimization, component-based frontend design, modular backend services, and knowledge graph governance provide complementary mechanisms for responsive operation, service modularity, and incremental expansion across product categories. These findings indicate that experience continuity depends on linking transactional records with operational states and recommendation logic through shared platform services. The resulting framework connects ownership records, maintenance states, recommendation logic, and supporting platform services within a coherent post-purchase architecture. The study concludes that integrating verified ownership information with maintenance processes and compatibility-aware recommendations provides a structured foundation for sustained digital engagement after purchase while supporting platform scalability and extensibility. The framework also establishes design considerations to guide subsequent empirical assessment of post-purchase platforms across product categories, customer contexts, and digital commerce environments
Macroscopic Growth and Development Characteristics of Matoa Wood Susilo Budi Husodo; Faradilla Faradilla; Rima H. S. Siburian; Helmy Y. Setiabudi
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.v6i4.1925

Abstract

The growth and development of Matoa (Pometia coreacea) from the seedling stage to maturity may take several decades, particularly for trees to develop large diameter stems with a high proportion of heartwood. The development of juvenile and mature wood, heartwood and sapwood formation, and other wood properties is influenced by growth rate, environmental conditions, and genetic characteristics, which ultimately affect wood quality. These variations can be evaluated through macroscopic wood characteristics. This study examined the growth and development characteristics of Pometia coreacea based on macroscopic observations of wood and bark. The results showed that Pometia coreacea wood had indistinct growth-ring boundaries, with the number of growth rings generally increasing with increasing wood diameter. The mean growth-ring width ranged from 0.47 to 1.83 cm, indicating variation in radial growth among diameter classes. As stem diameter increased, the proportion of heartwood increased, whereas the proportion of sapwood decreased. Differences in wood color were observed between the tip and base sections of the stem. The bark was predominantly brown, with greenish or white patches, and became progressively thicker as stem diameter increased. Macroscopically, Pometia coreacea exhibited predominantly straight grain, a characteristic young-coconut odor, moderately coarse texture, and hard wood. The wood also showed relatively narrow rays. These characteristics indicate that changes in stem diameter are associated with variations in growth-ring development, heartwood and sapwood proportions, bark thickness, and other macroscopic properties. Overall, the findings provide useful baseline information for understanding the growth and development of Pometia coreacea and for supporting wood identification, quality assessment, and potential utilization based on its macroscopic characteristics
Converged Planning and Design for OSP/ISP and 5G Densification: A Unified Framework for Telecommunications Network Engineering Mohit Upadhyay
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.v6i2.2022

Abstract

The large-scale deployment of 5G networks requires telecommunications providers to coordinate fiber-to-the-cell-site (FTTCS) infrastructure planning with radio access network (RAN) densification as an integrated engineering activity. However, these activities are frequently managed through separate workflows, teams, software tools, and implementation schedules, resulting in duplicated effort, inconsistent planning decisions, and limited coordination between transport infrastructure and radio deployment. This study develops and evaluates a converged Plan-Design-Build (PDB) framework that integrates FTTCS and RAN planning within a unified engineering process. The framework incorporates a common data model covering outside-plant and inside-plant fiber assets and wireless network elements; a software architecture that combines geospatial network design with radio-frequency propagation analysis; four analytical formulas for site prioritization and program performance measurement; and workflow governance mechanisms for coordinated planning, design, and construction. The framework was evaluated through an empirical assessment of five candidate 5G sites under conventional and converged planning conditions, with fiber infrastructure requirements and deployment activities compared across the two approaches. The results indicate that converged planning reduced the estimated fiber infrastructure cost by 64% while improving alignment between network design decisions and construction scheduling. The integrated process also reduced infrastructure duplication by coordinating transport requirements with radio deployment priorities before detailed design and construction began. These findings demonstrate that FTTCS and RAN integration can improve the consistency of engineering decisions and coordination across network domains. The proposed framework provides an engineering-oriented basis for telecommunications providers to operationalize integrated 5G access infrastructure planning, design, and construction through consistent data structures, analytical methods, and governance mechanisms
Legacy-to-Cloud Data Migration in Retail: Engineering the Enterprise Data Lake Transition for Omnichannel Analytics Saikrishna Ala
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.v6i1.2057

Abstract

National specialty retailers often operate fragmented data infrastructures spanning enterprise resource planning, point-of-sale, inventory, e-commerce, and loyalty systems, creating challenges in integrating legacy data environments with scalable cloud-based analytics. This article develops an engineering framework for migrating legacy data warehouse environments to centralized, cloud-capable data lakes while supporting the operational requirements of omnichannel retail. The framework addresses five interdependent engineering challenges: heterogeneous, multi-source data ingestion; Hive-based table design for mixed analytical workloads; dual-load processing for historical migration and incremental updates; data quality management across disparate sources; and elastic infrastructure sizing for seasonal demand variability. The framework is developed from practical engagement with retail and enterprise data lake implementations, including a multi-month data warehouse-to-data-lake migration conducted for a national specialty retailer. The resulting architecture organizes historical migration, continuous ingestion, data validation, storage design, and infrastructure scaling within an integrated engineering workflow. The analysis indicates that heterogeneous ingestion requires standardized data interfaces and source-specific handling, while dual-load processing must coordinate historical backfill with ongoing incremental updates to maintain data continuity. Data quality controls are incorporated throughout ingestion and transformation to improve consistency across heterogeneous sources, while elastic infrastructure sizing enables workload capacity to adapt to changing retail demand. The framework consequently provides a structured data foundation that supports customer personalization, demand forecasting, supply chain optimization, and omnichannel fulfillment without requiring separate application-specific data infrastructures. The work concludes that successful legacy-to-cloud migration in specialty retail depends on treating ingestion, storage, processing, validation, and infrastructure scaling as interconnected engineering components. The framework, therefore, offers a practical reference for data engineering practitioners and architects undertaking comparable modernization initiatives in complex retail environments
Digital Transformation of Work-Integrated Learning in Vocational Education: Microcredential Technology, Collaboration, and Industry Engagement Ricky Cahyasari Putra; Ikhsanudin Ikhsanudin; Ade Dwi Putra Janata
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.v6i4.1510

Abstract

Work-Integrated Learning (WIL) is a strategic approach bridging vocational education and industry requirements. This study investigates digitalized WIL implementation in Indonesian vocational schools, focusing on microcredential technology utilization, interdisciplinary collaboration, and industry engagement. A descriptive survey was conducted with 146 respondents from West Java vocational schools, predominantly mechanical engineering programs. Data were collected June-July 2025 using validated Likert-scale questionnaires covering microcredential technology utilization, collaboration, digital portfolio development, and credential-based assessment mechanisms. Most respondents had less than three years WIL experience, reflecting early adoption stages. Findings reveal 71.9% of respondents rated the use of digital and microcredential-enabling technology as Good to Excellent, particularly in documentation and portfolio development. Infrastructure assessment shows 78.1% achieving good to excellent equipment quality, with 84.2% demonstrating adequate laboratory conditions. Interdisciplinary collaboration was rated effective by 69.8% of respondents, demonstrating progress toward integrated project-based learning. Industry mentor engagement reached 67.8%, with active participation through Learning Management Systems (87.7% usage), video conferencing (91.8%), and digital portfolios (73.3%). Digital portfolio quality achieved 59.6% good to excellent ratings, while documentation systems showed 61.6% effectiveness; these two dimensions form the evidence layer on which microcredential issuance depends, indicating that the technological pre-conditions for badge-based credentialing are present but not yet consolidated. Comparative analysis revealed significant improvements in digital versus traditional WIL, with 27.3% average enhancement across learning outcomes (p 0.001), particularly portfolio quality (+42.9%) and industry readiness (+32.0%). Results highlight that microcredential-oriented digital transformation enhances WIL effectiveness through improved collaboration, transparency, and school-industry alignment. However, challenges include uneven adoption, limited infrastructure, and varying digital literacy levels. The study recommends expanding microcredential platforms and their issuance-verification infrastructure, comprehensive educator training, and strengthened industry partnerships while developing standardized frameworks for microcredential recognition, issuance, and quality assurance
The Effectiveness of E-Comic Media with a Contextual Approach in Junior High Schools Sri Wahyuni; Zam Zami Arliyan; Fertilia Ikashaum; Juitaning Mustika
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.v6i1.1637

Abstract

Digital technology offers opportunities to provide engaging and accessible learning media for mathematics education. This study aimed to examine the effectiveness of e-comic media integrated with a contextual approach in teaching linear equations and inequalities in one variable to seventh-grade students at SMP Negeri 7 Metro, Indonesia. The study employed a quasi-experimental pre-test–post-test control group design. The population consisted of eight seventh-grade classes, while the sample comprised 60 students: 30 students from class VII C as the experimental group and 30 students from class VII F as the control group. The experimental group learned using e-comic media with a contextual approach, whereas the control group received conventional instruction without the e-comic intervention. Data were collected through pre-test and post-test assessments and analyzed using normality and homogeneity tests followed by a paired-samples t-test. The Shapiro–Wilk test indicated that the analyzed data were normally distributed (W = 0.903, p = 0.156), while Levene’s test indicated homogeneous variance (F = 9.702, p = 0.081). The paired-samples t-test reported a statistically significant difference between pre-test and post-test scores, t(29) = ?15.789, p 0.001, with Cohen’s d = ?3.086. These findings suggest an improvement in students’ learning outcomes following the use of contextual e-comic media. The visual storytelling, simple language, and connection between mathematical concepts and everyday situations may help students engage with and understand the learning material more meaningfully. Therefore, contextual e-comic media can be considered a promising digital learning medium for mathematics instruction at the junior high school level. Further studies are recommended to examine its effectiveness over a longer period and across different mathematical topics and subject areas.
Real-Time Mobile Analytics Architectures for Distributed Enterprise Operations Kumar, Ashwin Krishnappa
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.v6i4.2042

Abstract

Enterprise mobile applications increasingly serve as primary interfaces for monitoring distributed operations. Yet the analytics pipelines supporting these applications are often designed around batch-oriented processing rather than sub-second interactions. This article examines the architectural factors that influence real-time responsiveness in mobile analytics pipelines for geographically distributed enterprises. An integrative literature synthesis was conducted by consolidating findings from studies on edge computing, mobile computation offloading, distributed time-series storage, containerized infrastructure, mobile network performance, and enterprise analytics adoption. The synthesized evidence was organized into a five-tier reference architecture consisting of the mobile client, edge tier, real-time analytics backbone, governance layer, and enterprise consumption layer. The analysis indicates that edge processing and storage architecture impose critical constraints on end-to-end responsiveness by determining where computation, filtering, aggregation, and data persistence occur. Computation offloading performance is further influenced by workload characteristics, device capabilities, and network conditions, indicating that offloading decisions cannot be evaluated in isolation from the execution environment. Evidence from published benchmarks also indicates that purpose-built time-series storage and container-based edge processing can support high-rate data ingestion and near-real-time aggregation. At the same time, field measurements of mobile networks demonstrate substantial variability in throughput, latency, and connectivity. These findings indicate that real-time responsiveness depends on the interaction among consistency requirements, computation offloading strategies, edge processing, storage architecture, and network variability. The resulting reference architecture integrates these factors into a coherent basis for analyzing latency constraints and architectural trade-offs in distributed enterprise analytics. The framework can support the systematic evaluation and design of mobile analytics pipelines intended for responsive, geographically distributed operational monitoring
GBAS: A Hybrid GRU–BiLSTM–Attention–SVM Framework for Multiclass Stunting-Status Classification in Riau Province, Indonesia Akmar Efendi; M. Khairul Anam; Apri Siswanto; Neysha Putri Arianda
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.v6i4.1926

Abstract

Stunting-status classification using structured anthropometric data presents several challenges, including class imbalance, heterogeneous predictor characteristics, limited sample size, and the risk of target-derived information artificially inflating model performance. This study proposes GRU–BiLSTM–Attention–SVM (GBAS), a hybrid framework that combines recurrent deep representation learning, bidirectional processing, attention-based representation weighting, and margin-based classification for multiclass stunting-status classification. The study used 569 cross-sectional child-growth records from Riau Province, Indonesia, comprising Normal, Stunted, and Severely Stunted classes. Before model development, data-quality and leakage controls were applied, including measurement-unit standardization, exclusion of variables with substantial unavailable information, control of repeated feature combinations during partitioning, and removal of target-derived nutritional indicators. The remaining predictors were numerically encoded and standardized using parameters estimated from the training data, while class weighting was applied to address class imbalance without synthetic oversampling. In GBAS, GRU and BiLSTM operate as representation-learning components over a consistently ordered structured-feature representation, attention weights the resulting latent representations, and SVM performs final classification. On the held-out test set of 114 observations, GBAS correctly classified 113 observations, achieving 99.12% accuracy, 99.13% weighted precision, 99.12% weighted recall, and 99.12% weighted F1-score. Under the same experimental setting, GBAS outperformed the evaluated SVM, GRU, and BiLSTM baselines, which achieved accuracies of 89.46%, 95.78%, and 97.30%, respectively. These findings support the feasibility of the integrated GBAS framework for structured stunting-status classification. However, the results remain specific to the Riau dataset, feature ordering, and experimental configuration and require further validation through larger datasets, stronger tabular baselines, feature-order sensitivity analysis, component-level ablation, and external evaluation

Page 73 of 78 | Total Record : 775

 71   72   73   74   75 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol 6, No 4 (2026) Vol 6, No 3 (2026) Vol 6, No 2 (2026) Vol 6, No 1 (2026) Vol 5, No 4 (2025) Vol 5, No 3 (2025) Vol 5, No 2 (2025) Vol 5, No 1 (2025) Vol 4, No 4 (2024) Vol 4, No 3 (2024) Vol 4, No 2 (2024) Vol 4, No 1 (2024) Vol 3, No 4 (2023) Vol 3, No 3 (2023) Vol 3, No 2 (2023) Vol 3, No 1 (2023) Vol 2, No 4 (2022) Vol 2, No 3 (2022) Vol 2, No 2 (2022) Vol 2, No 1 (2022) Vol 1, No 4 (2021) Vol 1, No 3 (2021) Vol 1, No 2 (2021) Vol 1, No 1 (2021) More Issue