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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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Applications of IoT-Enabled Smart Model: A Model For Enhancing Food Service Operation in Developing Countries Azmery Sultana; Md Masum Billah; Mir Maruf Ahmed; Rakin Sad Aftab; Mohammed Kaosar; Mohammad Shorif Uddin
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (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.v5i2.4937

Abstract

The dining sector in developing countries faces numerous challenges, including inefficiencies in order handling, resource management, and ensuring food quality and customer privacy. Traditional methods often lead to delays, errors, and dissatisfaction. This paper proposes a quick-witted, intelligent order-handling system utilizing the Internet of Things (IoT) to address these challenges and enhance the overall dining experience. We present a comprehensive approach to developing and implementing an IoT-based automated order-handling system tailored to restaurants' specific needs and challenges in developing countries, highlighting the importance of technology in enhancing operational efficiency and customer satisfaction. The proposed automated secure order-handling system using IoT demonstrates significant potential for improving efficiency and customer satisfaction in the dining sector. By addressing common problems through advanced technology, this system offers a sustainable solution that enhances the dining experience while ensuring food orders' validity, quality, and privacy. We analyzed the potential impact of implementing such a system in developing countries, focusing on economic and operational benefits.
Exploring The Metaverse: A Comprehensive Bibliometric Review Using Scopus Database Pooja Sehgal Tabeck; Vinamra Jain
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.v6i1.3717

Abstract

Metaverse is fast growing and emerging technology domain which has been adopted all around the world by organizations in different facets of business. The penetration of the internet and social media all around the world has paced the adoption where Gaming and social media companies are torch-bearers of the metaverse. As the metaverse becomes popular among various domains which include education, health, marketing, fashion, finance, and many more, the field of research has also seen the adoption of metaverse as a field of study by academicians around the world. Despite the growing domain of research, there is a dearth of review studies in the field of the metaverse, to fill the void authors conducted a bibliometric analysis. The Scopus database is taken into consideration to perform bibliometric analysis using the Vosviewer tool. The study identified the top publication and growth trends, domains, geographical distribution of documents and keyword analysis. Key results depict that as metaverse is related to technological advancements, the maximum research has also been done in the field of computer science and engineering. The contribution in the field from technologically advanced countries is highest, whereas from less developed countries the contribution in the field is negligible.
Unlocking User Satisfaction: A Delone & Mclean Is Success Model Approach To It Helpdesk Ticketing System Adoption Niky Purnama Putra; Astari Retnowardhani
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.v6i1.4469

Abstract

The IT Helpdesk Ticketing System application is used to submit requests for IT services and handle technical problems related to these services. This research aims to understand the factors that influence user satisfaction with this application, which is triggered by user dissatisfaction. The research method used is qualitative using the DeLone & McLean IS Success Model, which is implemented through the Partial Least Squares Structural Equation Modeling (SEM) framework. The research was conducted on 231 respondents who were surveyed online. The results showed that system quality, service quality, and level of system usage significantly affect user satisfaction. System and service quality contribute positively to user satisfaction, while the level of system usage also has a key role in determining the level of satisfaction. The implications of the findings emphasize the importance of paying attention to these aspects in system development and improvement, while increasing the level of usage to meet the needs and increase user satisfaction more effectively.
DCT and SVD Sparsity-Based Compressive Learning on Lettuces Classification Lutvi Murdiansyah Murdiansyah; Gelar Budiman; Indrarini Dyah Irawati; Sugondo Hadiyoso; A. V. Senthil Kumar
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.v6i1.4506

Abstract

Compressive Sensing (CS) technique in image compression represents efficient signal which offering solutions in image classification where the resources are constrained especially on a large image processing, storage resource, and computing performance. Compressive learning (CL) is a framework that integrates signal acquisition via compressed sensing (CS) and machine/deep learning for inference tasks directly on a small number of measurements, On the other hand, in real-world high-resolution (HR) data, where the image dataset is very limited CL, has the drawback of reduced accuracy under conditions of aggressive compression ratio. Here, a reconstruction method is necessary to maintain high levels of accuracy. To address this, we proposed a framework Deep Learning (DL) and Compressive Sensing that processing a small dataset of 92 images maintaining high accuracy. The framework developed in this paper employs processing sensing matrix A in compressive sensing with two transformation methods: DCT CL with Multi Neural Networks and the SVD method with GoogleNet framework. To maintain the same computation efficiency as DCT Compressive learning, SVD with GoogleNet framework provides a solution for object recognition, achieving accuracy values ranging from 89.47% to 63.15% for compression ratios of 3.97 to 31.75. This performance shows a linear tendency concerning the PSNR level, an index of signal reconstruction quality, and demonstrates an efficient process in the S matrix.
The Art of The Gacha Lure: Determinants of The Continuous Use of Mobile Role-Playing Games (RPG) With Gacha System in Indonesia Nyiayu Olivia Miranda Bakrie; Cellila Aditama; Lim Sanny
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.v6i1.4745

Abstract

The expansion of the mobile games industry should be attributed to the convenience of in-game purchases that are adopted by most mobile games in the market. In this study, we aim to investigate the relationship between determinants of continuous use of mobile RPG games with gacha system in Indonesia. We disseminated a questionnaire that was then filled in by 257 respondents. From a total of 257 results, we excluded 38 questionnaires due to non-completion as well as 8 questionnaires due to the unreliability of questionnaire answers. There were 211 questionnaires remaining for the model analysis. We proposed a total of 13 hypotheses which resulted in flow experience and satisfaction being positively associated with intention of continuous use. The findings of this study highlight how massive the effect of different type of RPG games affect the determinants of players in Indonesia.
Pre-trained BERT Architecture Analysis for Indonesian Question Answer Model Sudianto Sudianto
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.v6i1.4746

Abstract

Developing a question-and-answer system in Natural Language Processing (NLP) has become a major concern in the Indonesian language context. One of the main challenges in developing a question-and-answer system is the limited dataset, which can cause instability in system performance. The limitations of the dataset make it difficult for the question-and-answer model to understand and answer questions well. The proposed solution uses Transfer Learning with pre-trained models such as BERT. This research aims to analyze the performance of the BERT model, which has been adapted for question-and-answer tasks in Indonesian. The BERT model uses an Indonesian language dataset adapted specifically for question-and-answer tasks. A customization approach tunes BERT parameters according to the given training data. The results obtained; the model is improved by minimizing the loss function. Evaluation of the trained model shows that the best validation loss is 0.00057 after 150 epochs. In addition, through in-depth evaluation of the similarity of question texts, the BERT model can answer questions measurably, according to existing knowledge in the dataset.
A Combined MobileNetV2 and CBAM Model to Improve Classifying the Breast Cancer Ultrasound Images Muhammad Rakha; Mahmud Dwi Sulistiyo; Dewi Nasien; Muhammad Ridha
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.v6i1.4836

Abstract

Breast cancer is the main cause of death in women throughout the world. Early detection using ultrasound is very necessary to reduce cases of breast cancer. However, the ultrasound analysis process requires a lot of time and medical personnel because classification is difficult due to noise, complex texture, and subjective assessment. Previous studies were successful in ultrasound classification of breast cancer but required large computations and complex models. This research aims to overcome these shortcomings by using a lighter but more accurate model. We integrated the CBAM attention module into the MobileNetV2 model to improve breast cancer detection accuracy, speed up diagnosis, and reduce computational requirements. Gradient Weighted Class Activation Mapping (Grad-CAM) is used to improve classification explanations. Ultrasound images from two databases were combined to train, validate, and test this model. The test results show that MobileNetV2-CBAM achieves a test accuracy of 93%, higher than the complex models VGG-16 (80%), VGG-19 (82%), InceptionV3 (80%), and ResNet-50 (84%). CBAM is proven to improve MobileNetV2 performance with an 11% increase in accuracy. Grad-CAM visualization shows that MobileNetV2-CBAM can better focus on localizing important regions in breast cancer images, providing clearer explanations and assisting medical personnel in diagnosis.
Effects of Movement Restrictions on Consumer Consumption Tapash Kumar Saha; Md. Fazlul Karim Patwary; Faria Ahmed; Md. Biplob Hosen; Rashed Mazumder
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.v6i1.4851

Abstract

This study addresses the impact of movement restrictions, particularly during pandemics, on global consumer behavior, with a focus on grocery shopping. Despite the widespread effects, research on these changes remains limited, prompting the need to investigate hidden purchase patterns contributing to economic growth. Employing secondary data analysis, the study explores the effects of movement restrictions on customer consumption patterns, using K-means cluster analysis to identify distinct consumer segments. The findings highlight significant impacts on purchasing power, item prices, and consumption behavior, with a notable increase in item prices during the post-restriction period followed by a subsequent decline influenced by economic factors such as financial uncertainty and shifting priorities. This research contributes by shedding light on the dynamic nature of consumer behavior during and after movement restrictions, offering valuable insights for policymakers and businesses navigating the post-restriction economic landscape and informing strategies for economic recovery and growth.
Attacks Detection in Internet of Things Using Machine Learning Techniques: A Review Amer Dawood Saleem; Amer Abdulmajeed Abdulrahman
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.v6i1.4878

Abstract

The proliferation of IoT devices across sectors such as home automation, business, healthcare, and transportation has led to the generation of vast amounts of sensitive data. This widespread adoption has introduced significant security challenges and vulnerabilities. This study aims to analyze and evaluate machine learning (ML) and deep learning (DL) models for detecting malicious activities in IoT networks, with a focus on improving cybersecurity measures. We conducted a comprehensive review of various ML and DL models, including Random Forest, Decision Tree, HTA-GAN, Hybrid CNN-LSTM, and SVM. The study also includes an evaluation of the datasets used for identifying harmful data, ensuring effective detection of large-scale attacks in IoT ecosystems. Our findings indicate that these models enhance IoT security by deploying efficient intrusion detection systems (IDS) using reliable, large-scale datasets. The study highlights the performance of these models in balancing security and resource management, given the constraints of IoT devices.ML and DL approaches offer significant security benefits for IoT networks, despite the challenges associated with their implementation. The study underscores the importance of future research to address these challenges and further improve IoT security. The results provide valuable insights into the application of ML/DL models in IoT security, contributing to both theoretical knowledge and practical solutions for enhancing cybersecurity in IoT ecosystems.
A Sustainable Hybrid Off-Grid System Design for Isolated Island Considering Techno-Economic and Frequency Stability Analysis Candra Febri Nugraha; Lukman Subekti; Ahmad Adhiim Muthahhari; Budi Eko Prasetyo; Rizki Firmansyah Setya Budi
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.v6i1.4892

Abstract

Electrifying remote islands presents complex challenges. Currently, most remote areas in Indonesia rely on diesel fuel for their electricity supplies, contributing to escalating generation costs and environmental degradation. Aligned with the global net-zero emission goal, this study proposes the design of a hybrid off-grid system for Kabare Village in the Raja Ampat Islands, integrating techno-economic and frequency stability analyses. HOMER Pro was employed to identify the most optimal system configuration, while DIgSILENT PowerFactory was utilized to assess the frequency stability performance of the system. This study unveils that the optimal system combines existing generators, solar panels, and batteries, with a net present cost of $1.37 million. The optimal system delivers an 11.8% reduction in levelized cost of energy to $0.269/kWh, alongside a 25.6% decrease in both fuel consumption and greenhouse gas emissions compared to the existing system. Moreover, the system meets frequency stability metrics, even under extreme operational conditions. This study demonstrates that implementing a hybrid off-grid system in Kabare Village is not only technically and economically feasible but also a practical option. These findings are anticipated to assist the government in promoting the utilization of renewable energy sources, particularly in remote areas such as the islands of eastern Indonesia.

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