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Techne: Journal of Engineering, Technology and Industrial Applications
Published by Kalam Practica Media
ISSN : -     EISSN : 31246559     DOI : -
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation
Techne: Journal of Engineering, Technology and Industrial Applications is a peer-reviewed open-access journal dedicated to advancing scholarly work in engineering, applied technology, and industrial innovation. Techne publishes high-quality empirical research, technical reports, experimental studies, design analyses, case studies, and emerging technology reviews that contribute to the development and application of engineering solutions. The journal aims to bridge academic research and real-world technological practices by providing a platform for researchers, engineers, practitioners, and industry experts to disseminate new insights. Techne encourages submissions that demonstrate originality, methodological rigor, and practical value in supporting technological growth and industrial problem-solving. All submitted manuscripts undergo an objective and constructive review process conducted by experts in relevant fields. Techne is published by the Kalam Practica Research Group and operates under an open-access policy to ensure global accessibility of scientific knowledge. Scopes include (but are not limited to): Mechanical, electrical, and civil engineering Industrial systems and manufacturing technology Information technology and applied computing Automation, robotics, and control systems Energy systems and sustainable engineering Material science and industrial design Geospatial engineering and technical instrumentation Innovation, prototyping, and applied industrial research Techne welcomes interdisciplinary works and studies that integrate engineering with technology-driven industrial applications.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 42 Documents
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Examining How Mobile Application User Experience, Service Quality, and Social Interaction Affect Customer Satisfaction: A Quantitative Study in the Online Services Industry Abdullah Samad
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This study aims to analyze the influence of Mobile Application User Experience (MAUE), Service Quality (SQ), and Social Interaction (SI) on Customer Satisfaction (CS) in the online service industry. This study uses a quantitative approach with a survey method, where data is collected from 100 respondents who use online service applications. Data are analyzed using multiple linear regression tests to identify the relationship between independent variables and dependent variables. The results of the study indicate that the three independent variables have a positive and significant influence on customer satisfaction. The MAUE variable has the greatest influence with a coefficient value of 0.516, followed by SI with a coefficient of 0.223, and SQ with a coefficient of 0.182. The R² value of 0.614 indicates that 61.4% of the variation in customer satisfaction can be explained by this model. These findings support the theory of the Technology Acceptance Model (TAM) and SERVQUAL, and emphasize the importance of application experience, service quality, and social interaction in creating customer satisfaction. This study provides theoretical contributions to the existing literature and practical implications for companies to improve customer satisfaction through application development, service quality, and social interaction features.
Leveraging Digital Technologies for Urban Resilience: Addressing Economic, Social, and Environmental Challenges in Developing Country Cities Jose Antonio Dela Cruz
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This study aims to explore urban resilience strategies in developing countries in addressing social, economic, and environmental challenges, especially in rapidly urbanizing cities such as Dhaka, Nairobi, Mumbai, and Manila. The study analyzes secondary data from government reports, international agencies such as UN-Habitat and the World Bank, and academic literature to evaluate the effectiveness of green infrastructure, adaptive technologies, and local-based policies in enhancing urban resilience using a case study approach. The results show that local-based policies that take into account the social, economic, and environmental characteristics of each city are more effective than generic approaches. Green infrastructure, such as mangrove parks and water channels, and simple technologies, such as early warning systems, have been shown to have significant impacts in enhancing resilience to climate change and natural disasters. In addition, collaboration with international agencies plays an important role in providing technical and financial support to cities with limited resources.
Application of Geospatial Survey Technologies to Support Engineering and Industrial Development Megan L. Hart Megan L. Hart; Daniel J. Kim; Priya N. Iyer Priya N. Iyer
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

The rapid development of engineering and industrial projects has significantly increased the demand for accurate, efficient, and reliable spatial data. Geospatial survey technologies play a critical role in providing foundational information required for planning, construction, monitoring, and evaluation of engineering activities. Conventional survey methods are increasingly complemented by advanced geospatial technologies such as Global Navigation Satellite System (GNSS), total station, unmanned aerial vehicle (UAV) photogrammetry, and geographic information systems (GIS). This study aims to analyze the application of geospatial survey technologies in supporting engineering and industrial development through a descriptive-analytical approach. The research synthesizes technical principles, operational performance, accuracy characteristics, and implementation challenges of commonly used geospatial survey instruments in engineering projects. Data were obtained from technical documentation, standards, and relevant empirical studies, which were then analyzed to evaluate the effectiveness of each technology in different engineering contexts. The results indicate that the integration of modern geospatial survey technologies enhances spatial accuracy, reduces operational time, and improves decision-making quality in industrial development projects. Technological adoption is influenced by factors such as operator competence, environmental conditions, and system interoperability. This study contributes to applied geospatial engineering literature by providing a structured evaluation of survey technologies and their practical implications for engineering and industrial applications.
Comparative Analysis of Geospatial Survey Technologies for Engineering Project Efficiency and Accuracy Tsering Wangchuk; Sonam Dorji Sonam Dorji
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

The increasing complexity of engineering and industrial projects demands geospatial survey technologies that are not only accurate but also efficient in terms of time and operational resources. Total Station, GNSS Real-Time Kinematic (RTK), and Unmanned Aerial Vehicle (UAV) photogrammetry are widely adopted in contemporary engineering practices, yet their comparative performance characteristics remain context-dependent. This study aims to conduct a quantitative comparative analysis of these three geospatial survey technologies by evaluating positional accuracy, survey duration, and spatial coverage within engineering project environments. A comparative research design was applied using secondary and simulated field data derived from engineering survey scenarios. The analysis reveals distinct trade-offs between measurement precision and operational efficiency across technologies. Total Station demonstrates superior accuracy for localized measurements, GNSS RTK offers balanced performance for control point establishment, while UAV photogrammetry excels in rapid large-area data acquisition. The findings contribute to engineering decision-making by providing empirical guidance on technology selection based on project scale and accuracy requirements.
Geospatial Data Accuracy and Its Impact on Engineering Construction Performance Dewi Kartikasari; Budi Santoso Wirawan Budi Santoso Wirawan
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This study develops a quantitative, engineering-oriented framework to analyze error propagation across common construction survey workflows and to estimate its impact on quality and performance. A set of generic, case-based scenarios is defined for typical construction tasks: foundation grid and anchor bolt layout, road centerline and grade, pipeline alignment, steel column positioning, and earthwork volume estimation. For each scenario, spatial uncertainty is modeled using covariance-based propagation and Monte Carlo simulation, separating random and systematic error components. Performance is evaluated using engineering-relevant metrics, including probability of tolerance exceedance, expected rework frequency, and error-induced uncertainty in quantities. Results show that (1) control network uncertainty and coordinate transformation bias often dominate final construction errors, even when high-precision instruments are used; (2) vertical uncertainty drives large impacts on earthwork quantities and grade compliance, with asymmetric consequences compared to horizontal error; (3) systematic components, including datum inconsistencies and biased control, produce coherent shifts that are difficult to detect without independent checks and can produce high-cost failures; and (4) hybrid measurement strategies can reduce risk when they explicitly allocate instruments to tasks based on tolerance class and error budget rather than instrument availability. The article concludes with a practical decision framework for accuracy management, emphasizing uncertainty documentation, redundancy, acceptance criteria linked to error budgets, and workflow-level quality assurance. The contributions are intended to support evidence-based construction surveying and to provide applied engineering guidance suitable for industrial practice.
Reliability of Low-Cost Sensor-Based Structural Health Monitoring: Quantifying Uncertainty, Damage Detectability, and Decision Thresholds Nur Aisyah Ramadhani; Muhammad Rizky Maulana Muhammad Rizky Maulana; Putu Ayu Lestari Putu Ayu Lestari
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

The study compares a representative low-cost MEMS accelerometer system against a conventional piezoelectric accelerometer baseline using a combined experimental and simulation design. A set of generic structural configurations and damage scenarios (stiffness loss in a cantilever beam, connection loosening in a frame, and support degradation) is analyzed under realistic operational variability, including temperature-driven drift and ambient vibration excitation uncertainty. Performance is evaluated using metrics aligned with engineering decision-making: probability of detection versus false alarm rate, time-to-detection under rolling windows, confidence intervals for identified modal parameters, and risk-weighted threshold selection. Results show that (1) sensor noise and bias do not merely degrade parameter accuracy, but can shift optimal decision thresholds and inflate false alarm rates when operational variability is unmodeled; (2) low-cost sensors can support robust detection of moderate damage when combined with careful filtering, redundancy, and baseline updating, but detection of small stiffness changes is sensitive to window length, placement, and environmental compensation; (3) decision reliability improves substantially when thresholds are derived from uncertainty budgets and false alarm constraints rather than fixed percentage-change rules; and (4) multi-sensor fusion and periodic calibration reduce uncertainty enough to make low-cost monitoring viable for operational screening and prioritization, while high-consequence decisions still require confirmatory inspection or higher-grade instrumentation. The article concludes with practical guidance for deploying low-cost structural monitoring as a decision system, emphasizing uncertainty characterization, threshold governance, and verification pathways consistent with applied engineering practice.
End-to-End Survey Productivity in Engineering Construction: Modeling Time-to-Decision Under Accuracy Constraints Emma Johansson Emma Johansson; Noah Andersen; Pieter van Dijk Pieter van Dijk
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article develops an end-to-end productivity model that links decision latency to accuracy constraints and construction tolerances. The proposed framework defines time-to-decision as a stochastic process combining (i) base workflow time (setup, acquisition, QC, processing, integration, and review) and (ii) expected iteration time arising from tolerance exceedance risk, verification failure, and quality assurance requirements. Using a generic, case-based set of construction survey tasks (layout of tolerance-critical points, corridor alignment, grade control, progress mapping, and earthwork quantity reporting), the study evaluates three primary technologies (Total Station, GNSS RTK, and UAV photogrammetry) and hybrid workflows. Accuracy is represented using uncertainty budgets and probability of nonconformance, while productivity is expressed as expected time-to-decision and decision throughput under deadlines. Results demonstrate that (1) the fastest field method does not necessarily yield the fastest decision, because downstream processing and verification can dominate; (2) strict tolerances amplify iteration costs, making high-defensibility measurements decision-optimal even when field time is longer; (3) control quality and coordinate integrity can dominate decision latency by increasing rechecks and reconciliation; and (4) hybrid strategies that allocate instruments by tolerance class minimize expected decision time while preserving acceptance reliability. The findings provide actionable guidance for planning survey workflows as decision pipelines rather than isolated measurement activities, supporting evidence-based scheduling and quality management in engineering construction.
Wireless Structural Monitoring Under Real-World Constraints: Quantifying the Impact of Data Loss and Time Synchronization Errors on Damage Detectability Wei Zhang Wei Zhang; Liang Chen Liang Chen
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article develops a quantitative, engineering-oriented framework to evaluate how data loss and synchronization errors propagate through an operational monitoring pipeline and influence damage detectability, false alarm rate, and time-to-detection under rolling decision windows. The study models both independent packet loss and burst loss, represents synchronization error as a combination of clock drift and jitter, and assesses their effects on frequency-domain indicators, operational modal analysis outputs, and multivariate damage indices calibrated under false-alarm constraints. Using generic structural archetypes that represent common civil and building dynamics, the results show that (i) moderate average packet loss can be tolerated when loss is approximately independent, but comparable loss rates become materially harmful under bursty conditions because they reduce effective record length and degrade spectral averaging, (ii) synchronization jitter introduces phase inconsistency that disproportionately damages cross-sensor coherence and mode-shape estimation, causing multivariate indicators to lose discriminative power even when single-sensor frequency estimates remain stable, (iii) combined loss and timing errors can shift optimal thresholds and inflate nuisance alarms unless baseline distributions are constructed under matching network conditions, and (iv) mitigation strategies such as local buffering, time-stamping discipline, drift correction, and modest redundancy can recover most decision performance at far lower cost than upgrading sensors alone. The findings translate into practical design rules for wireless SHM deployments, including allowable loss and timing budgets as functions of the monitored frequency band, window length, and decision criticality, thereby supporting reliability-aware monitoring architectures suitable for applied engineering practice.
From Logs to Rankings: A Quantitative Framework for SEO Performance Diagnosis Using Server Data and Search Console Signals Ananya Sharma Ananya Sharma; Ravi Kumar Singh Ravi Kumar Singh
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article presents a quantitative framework for SEO performance diagnosis that integrates server log analysis, Google Search Console signals, and on-site telemetry to measure three controllable components of organic visibility: crawl efficiency, indexability, and ranking stability. The framework introduces operational metrics including crawl-to-index yield, waste rate by URL class, discovery latency for new pages, canonical consistency, and volatility indices for query clusters, and it proposes an engineering workflow that maps observed organic underperformance to testable hypotheses and prioritized interventions. A generic, non-site-specific case design is used to demonstrate how the framework distinguishes between growth constraints caused by crawl budget fragmentation, indexation suppression due to duplication and canonical conflicts, and ranking instability associated with performance regressions and thin semantic coverage. Results illustrate that log-derived crawl patterns frequently diverge from sitemap expectations and that large fractions of crawler activity can be consumed by low-value parameterized URLs, which reduces effective discovery of high-value pages, while Search Console data can reveal impression ceilings and click-through inefficiencies that remain invisible in traffic-only dashboards. The paper contributes applied guidance for practitioners by translating SEO into measurable system components, providing reproducible diagnostic steps, and emphasizing governance through monitoring and controlled experimentation rather than ad hoc optimization, thereby aligning SEO practice with engineering reliability principles suitable for OJS-based applied technology publication.
Building Reliable Organic Search Systems: Log-Based Analysis of Crawl Waste and Indexation Performance Tsering Wangchuk Tsering Wangchuk
Techne: Journal of Engineering, Technology and Industrial Applications Vol. 1 No. 1 (2025): Techne: Journal of Engineering, Technology and Industrial Applications
Publisher : Kalam Practica Media

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Abstract

This article proposes a quantitative, engineering-oriented diagnostic framework that integrates server log telemetry and Google Search Console signals to measure three operational components of SEO performance: crawl efficiency, indexation yield, and visibility volatility, with the goal of translating organic growth constraints into measurable bottlenecks and testable interventions. The framework introduces metrics such as crawl waste rate by URL class, crawl-to-index yield, canonical consistency ratio, discovery and refresh latency, position volatility index for query clusters, and CTR efficiency conditioned on position distribution, and it specifies a reliability workflow in which thresholds and targets are defined as service-level objectives for organic visibility rather than as ad hoc improvement goals. A generic, non-site-specific case design is used to demonstrate how the method distinguishes crawl-budget fragmentation driven by parameterized URL spaces from indexation suppression caused by canonical ambiguity and duplication, and from search outcome instability associated with performance regressions or intent cannibalization. Results show that sites can exhibit high crawler activity while simultaneously suffering low effective crawling of canonical assets, that indexation yield can be materially reduced by inconsistent canonical signals even when sitemaps are valid, and that volatility segmentation reveals which query clusters are constrained by unstable eligibility versus weak snippet competitiveness. The study contributes an applied approach suitable for engineering and applied technology contexts by emphasizing reproducible measurement, constraint localization, and reliability-oriented governance of SEO interventions.

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