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Journal of Applied Engineering and Technological Science (JAETS)
Published by Yayasan Pendidikan Riset dan Pengembangan Intelektual
ISSN : 27156087     EISSN : 27156079     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Journal of Applied Engineering and Technological Science (JAETS) is published by Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI), Pekanbaru, Indonesia. It is academic, online, open access, peer reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. Journal of Applied Engineering and Technological Science (JAETS) is published annually 2 times every June and Desember.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 358 Documents
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Empowering Higher Education: The Tech Advantage in Work Coordination and Risk Management for Financial Growth Rauf, Ummu Ajirah Rauf; Ahmed, Saif; Deli, Mazzlida Mat; Asha’ari, Maryam Jamilah; Jamil, ‘Ainul Huda; Abdullah, Mohd Hafizuddin Syah Bangaan; Abdullah, Siti Intan Nurdiana Wong
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i1.6364

Abstract

This study examined the relationship of work coordination and Enterprise Risk Management on financial performance in Malaysian public higher education (PHEs). It addresses the gaps on how work coordination and ERM could mitigate financial challenges such as dependence on tuition fees and limited government funding. The responses from 350 key informants across 20 Malaysian PHEs were analyzed using SEM analysis. The findings reveal that work coordination significantly enhances ERM implementation, and ERM implementation positively influence the financial performance, ERM also act as a mediator variable, which has a greater effect on financial performance through work coordination. The findings support the strategic role of ERM in facilitating links between organizational capabilities and financial sustainability. It thus practically recommends increasing capacity through governance structures, investing in digital tools for risk management, and engaging leaders to improve ERM effectiveness. Theoretically, this study extends the Resource-Based View, placing ERM as that critical resource that would turn coordinated efforts into measurable financial outcomes. This study closes the literature gap in risk management in higher education by integrating work coordination and ERM within a comprehensive model of financial sustainability that has pragmatic implications for policymakers and leaders of institutions in strengthening resilience within resource-constrained educational contexts.
Introducing B-Sweep: An Innovative Bird-Repelling Device Powered by Solar Cells and Sound Waves, Efficiently Protecting Against Bird Strikes in Airport Airsides Muhammad Rafli Fazal; Direstu Amalia; Jasmin Masyirianti; Akbar Nopriansyah Saputra; Yudhistira Agung Mahendra; Muhammad Khafid Ridwan; Sukahir Sukahir; Yeti Komalasari
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.4594

Abstract

The study aims to create a bird-repelling device called Bird-repelling with solar cell and sound wave energy efficient protection (B-SWEEP) to reduce the likelihood of bird strikes. The study employs a Research and Development (R&D) methodology, whereby data is gathered through a site survey to identify bird-highlighted places, including documentation of the quantity and variety of birds observed during a specific timeframe at the Politeknik Penerbangan Palembang—analysis conducted by measuring the range and power consumption effectiveness. The findings indicate that B-SWEEP generated sound waves at a distance of 100 meters with a maximum frequency of 500 Hz. The B-SWEEP test field is used six times, with a five-meter buffer between each experiment and the user. The purpose is to evaluate how well B-SWEEP can receive Wi-Fi. This test enables us to determine the distance at which B-SWEEP began to perform poorly when the user gave commands, and it helps improve B-SWEEP even further as a result of this research. It demonstrates how B-SWEEP deters birds in a field. Using solar panels for charging, B-SWEEP can function without electricity for one hour. Using an ESP32-CAM microcontroller to implement Internet of Things (IoT) technologies. Airport managers can recognize the kinds of birds that fly into the airside area with the help of this micro camera, including sparrows that are immediately linked to a telephone. Due to its sound and wave, the sweep audio signal might deter birds from nesting and visiting the airport airside. Integrating IoT-based automation technologies with renewable energy sources can facilitate the execution of the eco-airport initiative. Based on testing results and feedback from 51 respondents, improvements to B-SWEEP include enhancing usability by simplifying interface complexity and adjusting visual elements for greater appeal. Furthermore, expanding its capabilities to repel a wider range of animals through tailored ultrasonic technology would enhance its effectiveness and user satisfaction, making B-SWEEP a more versatile solution.
Solving Simulated Imbalanced Body Performance Data using A-SUWO and Tomek Link Algorithm Febryan Grady; Joel Rizky Wahidiyat; Abba Suganda Girsang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.4738

Abstract

This research examines the impact of various sampling techniques on the performance of classification models in the context of imbalanced datasets, employing the body performance dataset as a case study.  Many studies in this field analyze the effect of sampling techniques on a model performance, however they often begin with imbalance datasets, lacking a balanced baseline for comparison. This research addresses that gap by simulating an imbalanced dataset from an originally balanced dataset, obtaining a target reference point for evaluating the effectiveness of the sampling methods. The dataset is categorized into three versions: (1) a normal distribution, (2) a simulated imbalanced distribution, and (3) a synthesized dataset achieved through various data sampling techniques, including oversampling with Adaptive Semi-Unsupervised Weighted Oversampling (A-SUWO), undersampling with Tomek Link, and hybrid sampling combining both techniques. The primary objective of this research is to identify sampling techniques, when combined with model performance, closely match the performance observed in the original balanced dataset. Based on all experiments using Decision Tree, Random Forest, and K-Nearest Neighbors (KNN) as classifiers, both A-SUWO and Tomek Link led to overfitting due to discernible gap between the training and testing accuracy, averaging 0.21304. Despite overftting and general performance issue, the undersampling with Tomek Link obtained highest test accuracy (0.65023), outperforming A-SUWO (0.62883) and the hybrid approach (0.63568) on average. These findings highlight the importance of appropriate sampling techniques and optimizing model performance in imbalanced datasets.
An Empirical Study for Estimating Ultimate Bearing Capacity of Concrete Small-Pile Cluster in Soft Clays Suyuti Suyuti; Mukhlis Muslimin
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.4789

Abstract

Soft subgrades with shear strength, cu of 10 kPa to 25 kPa are given low bearing capacity and high settlement. Local government has been built infrastructure of embankment such unpaved road on the soft subgrade by using timber and bamboo materials (called “Cerucuk”) are very familiar for Indonesian local people. By developing load capacity of floating pile type, bamboo pile cluster was applied for Tol road in North the Java Island. However, bamboo material limited of life construction inside the soft ground, and exploitation of timber pile was violated environmental issue. Therefore, this research method is developed a new geometrical small - cluster pile by using concrete from local material or Igneus stone such as gravel and sand produced in quarry Ternate Island. Ultimate bearing capacity of single small - cluster pile installation modelled in soft subgrade tank. Then, observed by several block concretes and it is presented by empirical formulae. Finally, the ultimate load capacity of small-pile cluster in soft subgrade is obtained Qu of 15.92 kN and 19.79 kN for observation and calculation, respectively. Rearrange of piles can be increased load capacity of small-cluster pile in soft subgrade as spacing single pile by spacing 5Deq to 3Deq. Mostly load capacity of small-pile clusters should be calculated by using empirical method to provide bearing capacity based on geotechnical rule with laboratory and field soil investigation data and load standard for unpaved roads.  
Large-Scale Periodic Gust Generation and Spectral Analysis Approach for Characterization and Evaluation Berk Zaloglu; Oksan Cetiner
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.4901

Abstract

Generating a periodic continuous gust in a controlled manner and at sufficiently large scales for the gust encounter studies on MAV applications is a challenge. In order to achieve it a pitching and plunging flat-plate is utilized with aggressive motion profiles. A range of periodic functions in pitch and plunge axes are investigated for the motion of the gust generator. Significant and distinct vortices are measured with PIV in its wake. An in-depth spectral analysis of the velocity vector field of the wake is performed to investigate the generated gust characteristics since the aggressive motion profiles can produce uniform and/or weak gust characteristics.  To obtain the cases that simulate large-scale transverse wind gusts in a quasi-sinusoidal pattern, the PIV results are evaluated by using auto- and cross-spectral density plots of the entire flow field at the wake, ensuring the consistency of the gust characteristics for future gust wing encounter studies. Four cases in which the flat-plate moves with the quasi-feathering condition provide gusts that are useful to employ in MAV gust studies.
Bottle Design of Onion Chili Sauce using Kansei Engineering for SMEs in Indonesia Weldellin Tanawi; Syafina Aisha Fitori; Rida Zuraida
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.5167

Abstract

The SMEs industry in Indonesia keep growing significantly in the last 10 years, driven by digital channels such as e-commerce. One of Indonesia's popular food products is onion chili. However, the packaging design of the product is generic and may not be attractive or meet consumer expectations. This study aims to design the product packaging for onion chili using Kansei Engineering (KE) to increase its value. To aim for the objectives, this research was conducted in two stages, the first stage was to assess customer satisfaction and collected Kansei words that related to packaged onion chili. The satisfaction level was measured based on color, packaging durability, and packaging style. In the second stage, a questionnaire consisting of a packaged design checklist and Kansei words was developed. Then, the Kansei words were reduced using Principal Component Analysis (PCA) and obtained 3 main factors which are convenience, durability, and hygiene & attractiveness. The result was then followed by determining the elements of the new design based on Partial Least Square Regression (PLSR) and followed by design requirement analysis. Three proposed bottle designs were developed based on those 3 main factors as an alternative design for SMEs who sell this kind of product
The Role of Communities of Practice in Increasing Organizational Maturity Levels towards Digital Transformation: Case Study of Employee Cooperative Marcel Marcel; Meyliana Meyliana; Spits Warnas Harco Leslie Hendric; Tirta Nugraha Mursitama
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.5539

Abstract

Organizations looking to improve operational efficiency, customer service and innovation begin by embarking on digital transformation journey. Such transformation necessitates a radical shift in the way organizations execute and behave. Communities of Practice (CoPs) are central to this wavy journey towards agility. This paper presents the role of CoP to assist in advancing organizational maturity quality for successful digital transformation, focusing from a social learning perspective. This paper conducted a case study with an employee cooperative of one state-owned enterprise based in Jakarta, Indonesia using literature reviews and semi-structured interviews involving the perspective from managers, IT staffs as well general staff. This paper utilized the Deloitte Digital Maturity Model (DMM) to evaluate digital maturity levels in five areas: Strategy, Culture, Organization, Technology and Customer. Results suggest that CoPs encourage a learning, innovative culture supported by management strong support and flexible structures with digital collaboration tools embedded in this comprehensive structure as well purposeful continuous training. The cooperative's digital maturity is in the initial stages, with five areas identified for improvement in strategy integration, cultural openness, organizational structure, technological adoption, and customer engagement. This research underlines that CoPs play an important role in enabling collaborative learning as well as digital maturity. Future research could elaborate on the long-term consequences of CoP and extend comparisons across various industries as well as consider how emerging technology influences a variety of factors related to effectiveness of CoPs.
Flexible Job Shop Scheduling Optimization Using Genetic Algorithm For Handling Dynamic Factors Masmur Tarigan; Ford Lumban Gaol; Alexander AS Gunawan; Widodo Budiharto
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.5784

Abstract

This research introduces the Genetic Adaptive Scheduling System (GASS), a novel framework designed to optimize scheduling in Flexible Job Shop Scheduling Problems (FJSP). Due to its complexity, FJSP presents significant challenges stemming from machine flexibility, dynamic routing, and operation precedence constraints. GASS addresses these challenges by incorporating real-time, dynamic data, enabling the system to adapt to machine downtimes, fluctuating job priorities, and process variability. Leveraging advanced genetic algorithm techniques, GASS integrates enhanced mutation and selection processes that dynamically adjust setup times, prioritize urgent tasks, and balance machine workloads to minimize makespan effectively. Empirical results demonstrate that GASS achieves up to a 45.3% reduction in makespan within the flexible packaging industry, showcasing its ability to enhance scheduling efficiency and adaptability. The research highlights the system’s scalability and potential applicability across diverse industries, including printing, electronics, pharmaceuticals, and food manufacturing, where operational flexibility and efficiency are critical. By bridging existing gaps and integrating real-time constraints into scheduling models, GASS provides practical solutions for modern manufacturing environments. The findings contribute to the advancement of optimization techniques in FJSP, offering valuable insights for researchers and practitioners seeking efficient, scalable, and adaptive scheduling systems.
Magic Boom Chemical: A Tracking Marker-Based Approach in Developing Chemical Molecule Textbook Tina Tri Wulansari; Pebiansyah Hafsari; Ratih Fenty Anggriani Bintoro; Yuli Fitrianto; Gunawan Gunawan; Nyoman Santiyadnya; Reza Andrea; Syafei Karim; Dewi Rostia; Guntur Arie Wibowo; Tri Hannanto Saputra; Maria Floriana Ping
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.5890

Abstract

In Traditional teaching methods for chemical molecules, which rely on textbooks and physical modeling tools, face challenges in providing an engaging and comprehensive learning experience. This study introduces "Magic Boom Chemical," an augmented reality (AR)-based educational tool utilizing marker tracking to display three-dimensional molecular structures. A quasi-experimental method was employed, involving two groups of high school students: an experimental group using the AR application and a control group using conventional teaching methods. Pre-tests and post-tests were conducted to assess the effectiveness of the tool. Results indicated a significant improvement in students’ understanding and engagement when using the AR-based media, with the experimental group achieving higher average post-test scores. The study concludes that integrating AR into educational materials can enhance learning outcomes and increase students’ motivation. These findings highlight the potential of AR technology as an innovative solution for improving science education and suggest further research to refine and expand its applications.
The Comparison of Activation Functions in Feature Extraction Layer using Sharpen Filter Oktavia Citra Resmi Rachmawati; Ali Ridho Barakbah; Tita Karlita
Journal of Applied Engineering and Technological Science (JAETS) Vol. 6 No. 2 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v6i2.5895

Abstract

Activation functions are a critical component in the feature extraction layer of deep learning models, influencing their ability to identify patterns and extract meaningful features from input data. This study investigates the impact of five widely used activation functions—ReLU, SELU, ELU, sigmoid, and tanh—on convolutional neural network (CNN) performance when combined with sharpening filters for feature extraction. Using a custom-built CNN program module within the researchers’ machine learning library, Analytical Libraries for Intelligent-computing (ALI), the performance of each activation function was evaluated by analyzing mean squared error (MSE) values obtained during the training process. The findings revealed that ReLU consistently outperformed other activation functions by achieving the lowest MSE values, making it the most effective choice for feature extraction tasks using sharpening filters. This study provides practical and theoretical insights, highlighting the significance of selecting suitable activation functions to enhance CNN performance. These findings contribute to optimizing CNN architectures, offering a valuable reference for future work in image processing and other machine-learning applications that rely on feature extraction layers. Additionally, this research underscores the importance of activation function selection as a fundamental consideration in deep learning model design.

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