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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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Proximity Index Value for Supplier Selection Using Compromise Weighting of Stepwise Weight Assessment Ratio Analysis and The Method of Removal Effects Of Criteria: A Case Study in Indonesian Leather Industry Agus Ristono
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.v6i1.6030

Abstract

Procurement of new raw materials is needed when product demand increases, and raw material suppliers must be determined to meet the company's needs. This research examines what criteria a company needs when selecting criteria using Delphi. The weighting of criteria cannot be separated from the element of the decision maker's subjectivity; therefore, it is necessary to compromise between subjective and objective criteria. Therefore, the study used The Method of Removal Effects of Criteria (objective weighting of criteria) and Stepwise Weight Assessment Ratio Analysis (subjective weighting of criteria) in weighting criteria. Then, considering the weight of the criteria, the Proximity Index Value (PIV) is used to evaluate and rate the suppliers. The offered methodology is applied to a real case study from a leather manufacturing company in Indonesia to verify its applicability with a sensitivity analysis performed on different scenarios. The findings indicated that the proposed model is dependable and that the rankings are resilient to fluctuations in the criterion weights.
An Enhanced Image Segmentation Technique-Based on Motion Detection Algorithm Zaid Sh. Bakr; Hamzah M. Marhoon; Ammar Alaythawy
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.v6i1.6080

Abstract

This paper presents a prototype for an intelligent, self-contained theft detection system designed for small-scale applications. Utilizing a Raspberry Pi 3 as the core processing unit, the system employs a motion-detecting camera to monitor a defined area, recording and securely archiving video data on a cloud server upon detecting movement. This cloud-based repository supports real-time analysis, ensuring that data remains available for future reference. Battery-powered configuration enhances the system’s portability, making it adaptable across various environments, such as healthcare for patient monitoring or wildlife tracking for behavioural studies. The design aligns with IoT principles, featuring autonomous operation and cloud connectivity, offering a scalable, flexible solution capable of integration into larger IoT ecosystems for diverse surveillance applications.
Effect of Zinc Addition in Copper to Structure, Hardness, Corrosion, and Antibacterial Activity Lisa Samura; Mustamina Maulani; Cahaya Rosyidan; Kartika Fajarwati Hartono; Suryo Prakoso; Evi Ulina Margareta Situmorang; Daniel Edbert; Bambang Soegijono; Muhammad Yunan Hasbi; Ferry Budhi Susetyo
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.v6i1.6098

Abstract

Brass (CuZn) is widely used today due to better mechanical, thermal, and chemical properties. The present research fabricated CuZn alloy by adding various Zn (6, 9, and 12 wt.%) to the Cu using gravity casting. Casts CuZn alloy by adding various Zn to the Cu to investigate optimum composition were resulting highest inhibited of bacterial activity. In addition, the structure, hardness, and electrochemical behavior of the alloy were also investigated using XRD, Vickers hardness, and potentiostat equipment. XRD confirmed that CuZn alloy has an alpha phase, and a FCC crystal structure. The rise of the Zn content in the alloy led to an increase in crystallite size, a decrease in the hardness and a shift to a more negative OCP potential at 1200 s measurement. Enhancing the Zn content to 9 wt.% in the alloy lead to decrease the corrosion rate. Moreover, 24-hour post-contact observation found that the sample places removed remained clear of bacteria. The Cu6Zn sample successfully inhibited the growth of Escherichia coli in the 3rd hour, while Staphylococcus aureus was 100 % reduced in the 7th hour. The Cu6Zn sample could be used as an alternative material for medical equipment in ambulances.
Students’ Activeness Measure in Moodle Learning Management System Using Machine Learning Chandrakumar Thangavel; Valliammai S E; Amritha P. P; Karthik Chandran; Subrata Chowdhury; Nguyen Thi Thu; Bo Quoc Bao; Duc-Tan Tran; Duc-Nghia Tran; Do Quang Trang
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.v6i1.6128

Abstract

Due to COVID-19, the need for online education has increased worldwide, prompting students to shift from traditional learning methods to online platforms as guided by higher education departments. Higher learning institutes are focused on developing constructive online learning platforms. This research aims to measure students’ academic performance on an online learning platform – Moodle Learning Management System (LMS) – using machine learning techniques. Moodle LMS, a popular free and open-source system, has seen significant growth since the COVID-19 lockdown. Many researchers have analyzed student performance in online learning, yet there remains a need to predict academic outcomes effectively. In this study, data were collected from a higher learning institute in Tamil Nadu, and linear regression was applied to predict students' final course outcomes. The analysis, based on students' activity in Moodle LMS across both theory and laboratory courses, helps faculty identify students at risk of failing and adjust instructional methods and assignments accordingly. This approach aims to reduce failure rates by providing timely warnings and encouraging students to improve their engagement with LMS resources.
Air-Gap Reduction and Antenna Positioning of an X-Band Bow Tie Slot Antenna on 2U CubeSats Boutaina Benhmimou; Fouad Omari; Nancy Gupta; Khalid El Khadiri; Rachid Ahl Laamara; Mohamed El Bakkali
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.v6i1.6158

Abstract

In this research work, a small size and wide-band Bow Tie slot antenna (BTSA) is proposed and optimized for use on an unlimited lifetime small-sized CubeSats at X-band. Interestingly, this paper introduces a graceful mechanism of integrating Bow Tie slot antennas on the bodies of small CubeSat configurations, which minimizes the antenna throwing from the satellite body and the whole CubeSat volume. The proposed approaches propose and analyze in detail how a small metallic part of a 2U CubeSat body improves the antenna performances around an operating frequency of 8.4 GHz. It maximizes the antenna gain simultaneously with the beamwidth angles at 8.4 GHz by suppressing the resulting back-lobes, which are re-directed outside the CubeSat box. These impacts are achieved by shifting a very small air-gap distance of only 1 mm between the back face of the BTSA dielectric and the CubeSat top face. The developed BTSA is lightweight and exhibits a unidirectional radiation pattern with a wide beamwidth angle of about 160° and a high gain of about 11.0 dBi at 8.4 GHz. The overall results with occupied size and volume are satisfactory for unlimited lifetime CubeSat missions at X-band such as UM5-Ribat and UM5-EOSAT of University Mohammed V in Rabat.
Oil Palm Smallholders Entrepreneurs And Financial Literacy: Technology Adoption Mara Ridhuan Che Abdul Rahman; Ummu Ajirah Abdul Rauf; Suguna Sinniah
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.v6i1.6168

Abstract

This study explores the relationship between financial literacy and business performance among oil palm smallholder entrepreneurs in Malaysia, emphasizing the role of technology in improving financial practices. Many smallholders earn less than RM2000 per month, largely due to low financial literacy, which hinders effective financial management and business sustainability. Financial literacy is crucial for accessing financing and making informed financial decisions. Data were collected from 1,500 smallholders across six territories in Malaysia, with a 14.4% response rate. Structural Equation Modeling (SEM) revealed a positive correlation between financial literacy and improved financial practices, leading to better business outcomes, including enhanced access to bank loans and government grants. The study also highlights the transformative potential of digital technologies, such as mobile banking and financial education apps, in bridging financial literacy gaps. The findings suggest that targeted financial literacy programs and the adoption of digital tools can significantly enhance smallholders' financial management and business performance. This has important implications for policymakers and financial institutions in promoting rural economic development and sustainable entrepreneurship within the agricultural sector.
Advanced Smart Bracelet for Elderly: Combining Temperature Monitoring and GPS Tracking Sugondo Hadiyoso; Indrarini Dyah Irawati; Akhmad Alfaruq; Tasya Chairunnisa; Muhamad Roihan; Suyatno Suyatno
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.v6i1.6182

Abstract

Indonesia is entering an aging population period, marked by an increase in the number of elderly individuals, accompanied by a rise in dementia cases. This situation leads to higher dependency among the elderly on others for assistance or long-term care. Dementia can cause elderly people to lose their sense of direction, often wandering aimlessly, making them difficult to track. To address this issue, a wearable smart bracelet is proposed to monitor the location and a vital body parameter such as body temperature. The system is equipped with a tracking application that can send an alert if the user is outside a designated area. It automatically sends a warning message to the caregiver's or family member's smartphone when abnormal signs are detected. The bracelet is designed like a wristwatch, to be worn on the wrist. It is small, lightweight, and battery-operated. Temperature and location data can be transmitted in real-time using an internet network to mobile devices. The device can notify when the user is outside the specified area. Test results indicate that the device has high accuracy and reliability in monitoring location and body temperature with accuracy around 98.5%, as well as sending notifications through a Telegram bot when certain thresholds are exceeded. This device can work properly for up to 5 hours on a single battery charge. With this device, it is expected to help monitor and support the care of the elderly so that they can improve their quality of life. This device can also provide an emergency alarm if the elderly are outside the area.
Software Design for Inventory Management Improvement in a Peruvian National University Velasquez, Linett; Rubiños , Santiago; Grados , Junior; Grados, Juan; Marrujo, Claudia
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.v6i1.6225

Abstract

The purpose of this study was to design a software to optimize inventory management in the Office of Information Technology and Communications (OTIC) of the Faculty of Industrial Engineering and Systems of the Universidad Nacional del Callao, Peru. The research arose due to the lack of an efficient system that minimizes asset losses and reduces operational errors in the university context, where resource constraints demand sustainable and adaptable solutions. To address this problem, an agile methodological approach was used, implementing the Scrum methodology in the software design, as well as an architecture based on MVC (Model-View-Controller) with technologies such as MySQL, PHP and CodeIgniter. The evaluation of the system included usability surveys to users and an expert judgment, focused on three dimensions: Reliability, Usability and Design. The results of the study showed a high acceptance of the system in terms of ease of use and user satisfaction, highlighting the effectiveness of the modular design for future extensibility and performance improvements. This study provides theoretical value by highlighting the application of agile methodologies in educational environments and highlights the importance of a scalable design to improve inventory management in academic institutions. In practical terms, the implementation of this software offers an adaptable and scalable solution, with potential for replication in other universities, optimizing resource management and strengthening operational efficiency in the educational sector. The main contribution of the study lies in the combination of a flexible and low-cost design, aimed at meeting the specific needs of inventory management in educational environments with budgetary constraints.
Big Data and Netnography Analysis of Mental Health on Twitter/X: Evidence From Indonesia Tika Mutia; Jenny Ratna Suminar; Susanne Dida; Herlina Agustin
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.v6i1.6226

Abstract

Digital traces of mental health conversations on social media X have become a new culture, especially for the young generation. This study aimed to explain the network, themes and comment of social media discussion posts about mental health in Indonesia. This study has focused on each conversation in the form of tweets using big data analysis from posts with containing keyword related and specific criteria on the theme of mental health. This research was collected 15,200 mental health-themed discussions on X. Further, the researcher conducted a selection based on engagement and specific criteria through the NoLimit tool in 2021. A total of 4969 threads were analyzed further. As a result, researchers found a network that formed 3 clusters, namely the Stress cluster, Depression cluster, and Bipolar cluster. Apart from that, three big themes were found that represent every conversation on social media X in Indonesia, namely, (1) The Story of Survivors, (2) Mental Health as a Trend and Fashion, (3) Stress, Anxiety, or just a Gerd? Through the study of netnography, it is revealed that social media serves as a community's backbone while also perpetuating stigma related to mental health issues. Mental health in Indonesia is still an issue that does not get serious attention, even though the number of cases of mental disorders continues to increase.
Deep Learning Techniques for MRI Image-Based Performance Analysis of Brain Tumor Classification Renuga S; Malathi P; Shamija Sherryl R.M.R; Anuradha T; Mishmala Sushith; Senthil Kumar A
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.v6i1.6288

Abstract

Brain tumors can produce symptoms and indicators due to direct tissue death, localized invasion of the brain, or aftereffects from increased intracranial pressure. In order to identify images from the publicly available image dataset, this work combined multiple image feature sources using deep learning algorithms. The architecture of most classic convolutional neural networks (CNNs) consists of convolution modification and max-pooling of layers connected with several completely linked layers. The steps used in this system are pre-processing, segmentation, feature extraction, and classification. The preprocessing procedures of this investigation were used by the modified trimmed median filtering approach. U-Net segmentation is used to carry out the segmentation process. Features are then extracted using the wavelet transform method. In this study, MRI images of brain tumors, including meningnant and benign tumors, were detected and classified using the proposed CNN-based VGG16 model. The convolutional neural network (CNN) architectures employed in this investigation were guided by the VGG-16. The outcomes are assessed in terms of accuracy, precision, recall, and F1-score after the suggested model has been simulated. According on the test findings, the recommended approach may lead to 96.9% maximum recall, 97.4% maximum F1-score, 98.45% maximum accuracy, and 98.1% maximum precision.

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