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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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The Paradox of Smart Tourism: Does Technology Empower or Discourage Experience Sharing Sari, Mareta Kemala; Lita, Ratni Prima; Lenggogeni, Sari; Ma'ruf, Ma'ruf
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7353

Abstract

This study aimed to develop a model for showing the process of sharing memorable experiences created at tourists destinations or digital tourism supported by smart tourism technology (STT). A survey was conducted on 136 tourists who stayed in home-based accommodations and shared experiences on Instagram, which were later reposted by the destination's official Instagram account. In this study, a quantitative method was used, and the questions were addressed using the SMART PLS 4.1.0.9 tool. Furthermore, data were collected using a purposive sampling method from 136 visitors in West Sumatra who had completed their stay, shared experiences in the form of photos or videos on social media, and had posts reposted by the destination’s official account. The results showed that tourists tended to place greater importance on the emotions evoked by travel experiences compared to those arising from interaction with smart tourism technology (STT) services when evaluating overall happiness. Both theoretical insights and practical applications were further discussed.
Artificial Intelligence and Optimization of Reverse Logistics: An Analysis in the Aquatic Industry of The Mekong Delta Tran Trung, Chuyen; Trinh, Phan Tran Xuan; Huy, Tran Thanh; Khiem, Nguyen Tri; Tac, Nguyen Van
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7471

Abstract

In recent years, artificial intelligence (AI) has become an important technology that enhances the competitive advantages for businesses. This study investigates the application of artificial intelligence and how it can optimize reverse logistics for the aquatic industry in the Mekong Delta. It also explores the current situation in applying AI, its benefits, and challenges when using AI in reverse logistics for aquatic enterprises. The research uses qualitative and quantitative methods to collect data from interviewing managers, logistics staff, and technicians to deliver a survey to 41 seafood businesses. Results show AI applications in forecasting, storage, and recycling can cut operational costs by over 10% for 46.3% of firms and improve recovery time by over 10% for 56.1%. Benefits also include higher operational efficiency and better environmental performance. However, challenges persist in system integration, data access, and workforce readiness. The study provides practical recommendations, including enhancing AI workforce training, system integration, and collaboration with technology providers, to help seafood companies overcome barriers and maximize the benefits of AI in reverse logistics.
Generating Accurate Topographic Map by Integrating Drone Imagery and GNSS Data Abdulhassan, Aqeel A.; Alwan, Noor A.; Azeez, Marwaa K.; Yaseen, Doaa T.
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7532

Abstract

When operating in big or hard-to-reach areas, traditional topographic survey methods can be costly, difficult to organize, and time-consuming. Some of these technologies use total stations and GPS on the ground and aerial photogrammetry done by planes or helicopters. We need a better and cheaper approach to collect geographic data fast. This article discusses employing unmanned aerial vehicles (UAVs) for topographic surveying, mapping, and updating data as one option. A DJI Mavic 2 Pro quadcopter drone with a 20-megapixel digital camera took photographs of the Wasit University campus from 125 meters above the ground. The pictures indicated a space of around 0.43 km², with 80% of the front and 70% of the sides overlapping. The research area was turned into an orthomosaic by Agisoft PhotoScan Professional. This was then loaded into ArcMap so that features may be taken out. By comparing the coordinates of fourteen Ground Control Points (GCPs) that we got using the Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) mechanism, we were able to get a reference positional precision of 0.050 m RMSE. The results of this study demonstrate that geospatial data obtained from UAVs, when augmented by GCPs, can produce and update comprehensive maps with accuracy comparable to RTK GNSS and Total Station methodologies. Many individuals use these methods for surveys of land, buildings, and engineering.
Acceptance of Culture Mobile Tourism Among Tourist: A Model Development Study Syaifullah, Syaifullah; Ariffin, Shamsul Arrieya; Nordin, Norhisham Mohamad
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7588

Abstract

This study is a preliminary study on the development of a new model by combining and integrating existing models, namely the Technology Acceptance Model (TAM) and Hofstede's Culture Dimension. The development of this model was carried out using IPO logic (input-process-output) and a causal model by combining, adopting, and adapting previous models. The influence of the formed path consists of 17 links and produces 10 variables. The existing variables will be formed into 40 indicators. This study examines the impact of cultural values on tourists' perceptions of usefulness, ease of use, trust, and conditions that support mobile tourism technology. This study also investigates the mediating role of cultural dimensions on behavioral intentions to use mobile tourism. This study intends to provide important information in developing and implementing more effective and sensitive mobile tourism by incorporating cultural dimensions into the TAM framework. These findings will provide extensive information to stakeholders about tourism improvement and the importance of cultural adaptation in adopting mobile tourism.
Multipurpose Incubator Based on Microcontroller System With Distance Monitoring Feature Case Study For Crackers Drying Supriyono, Heru; Juliana, Anik; Supardi, Agus; Kurnia, Pramudya; Ananta, Muhammad Satria; Nugroho, Mohammad Dwiki Aji; Hidayatullah, Helmi
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7604

Abstract

Most available commercial incubators are considered not appropriate for certain food processing such as for crackers drying and also considerably expensive. Besides, they do not have distance monitoring and control features. The objective of this article is to present the development process of an incubator prototype which has distance monitoring and control feature built based on the components commercially available in the market involving  traditional stove-based oven, electric heater, DHT22 temperature sensor, ESP8266 microcontroller, buzzer, and LCD OLED display. The incubator was equipped with the Blynk platform of a smartphone for distance control and monitoring. The functional test results showed that the developed incubator works well as expected. The calibration testing results suggested that temperature measurement by using the developed system has inaccuracy of 0.34% when compared to measurement by using a commercial thermometer. To validate its function in actual condition, the incubator was used for drying rice crackers. The rice crackers were dried at the temperature of 70  with a duration of 5 hours. It can be observed that the drying result by using the developed incubator was comparable to that of drying by direct sunlight on a sunny day with a duration of 16 hours.
From Exclusion to Empowerment: Redesigning E-Learning to Mitigate Risks for Disabled Students Rauf, Ummu Ajirah Abdul; Deli, Mazzlida Mat; Husin, Nanang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7608

Abstract

This study explores how e-learning platforms can be redesigned to empower disabled students by mitigating their educational risks, such as accessibility barriers, communication challenges, and unequal participation. Using a qualitative approach, the research combines literature reviews, case studies, and user feedback to analyze current e-learning environments. It evaluates how AI technologies like ChatGPT can facilitate content accessibility, improve interaction, and support personalized learning experiences for disabled students. This study identifies key risks: limited content adaptability, poor user interface design, and social isolation, which hinder disabled students' academic engagement. It proposes a framework integrating assistive AI tools to transform these platforms into inclusive, low-risk learning environments. Results indicate that AI-driven adaptations can enhance content comprehension, foster collaboration, and improve learning outcomes for disabled students. This study focuses on higher education contexts and may require further validation across diverse educational levels and technological infrastructures. Additionally, reliance on evolving AI technology presents challenges related to affordability and accessibility. This study contributes to the growing field of inclusive education by offering a novel, AI-supported framework to redesign e-learning platforms. It addresses the gap between technological advancement and practical accessibility solutions, emphasizing risk mitigation for disabled students. The findings provide valuable insights for educators, policymakers, and technology developers aiming to create equitable, empowering learning experiences for all learners.
Swarm Intelligence Optimisation Vs Deep Learning: Energy-Aware Strategy for Disaster Communication Networks Mansor, Norhisham; Md Shah, Wahidah; Khambari, Najwan
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.7937

Abstract

In disaster-prone environments, communication networks must sustain operation under severe constraints such as limited energy, damaged infrastructure, and uncertain topology. This study compares Deep Learning (DL) and Swarm Intelligence Optimisation (SIO) as energy-aware strategies for disaster communication. While DL excels in data-rich prediction and situational analysis, its reliance on high-performance hardware and stable connectivity restricts its feasibility during real-time emergencies. In contrast, SIO provides decentralised coordination, lightweight computation, and adaptive routing, making it better suited to infrastructure-independent device-to-device (D2D) networks when central control collapses. A comparative conceptual framework was developed to evaluate both paradigms across five criteria: energy efficiency, adaptability, computational demand, response time, and scalability, based on recent literature between 2023 and 2025. Findings show that SIO demonstrates superior suitability for energy-limited and time-critical operations, while DL remains valuable for pre-disaster prediction and post-event analysis. Hybrid DL–SIO frameworks bridge both paradigms, enabling predictive–adaptive synergy across the disaster lifecycle. The study contributes a context-aware guideline for algorithm selection, shifting the focus from technology-centric performance toward environment-centric deployment in future energy-efficient, resilient, and adaptive disaster communication systems.
Ergonomic Study in Developing The Organizational Culture to Improve SME's Performance Nurwildani, Mohammad Fajar; Purnomo, Hari; Soewardi, Hartomo; Kusrini, Elisa
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.8084

Abstract

In industrial companies, both large and small-scale, performance is the main indicator of organizational success. Optimal performance can be achieved if the organization implements a healthy and effective organizational culture. On the contrary, an improper organizational culture can lead to conflicts between employees and stakeholders. Conflicts often arise that can cause work discomfort. The impact is to reduce work morale, negatively impacting performance and leading to a decline. Therefore, organizations need to build a culture that considers the human factor. One approach that can be applied is the concept of ergonomics, which integrates physical, cognitive, and organizational aspects to create a comfortable work environment so that employees can work healthily and effectively. This study aims to analyze the role of ergonomics on organizational culture and its implications in improving worker performance in the SME environment. This study uses a quantitative approach, supported by field observations and structured interviews with workers and managers of SMEs. Data analysis was carried out using the Structural Equation Modeling (SEM) method. The results of the study show that ergonomic aspects that have a significant effect on the formation of organizational culture with a loading factor value greater than 0.7 include physical ergonomics through workload variables (with work duration indicators), work environment variables (with temperature, humidity, lighting, and noise indicators), and equipment and equipment variables (with indicators of tool and machine design conditions, cognitive ergonomics (with indicators of perception, logical reasoning, and working relationships); and organizational ergonomics through work system design variables (with communication indicators and task variations) and work organization variables (with organizational structure indicators). These findings confirm that improving ergonomics not only creates a healthier and more efficient work environment but also strengthens organizational cultural values, which ultimately positively impacts the overall performance of SMEs
Evaluation of Water Needs and Availability in The Design of The Water Needs Masterplan on The IPDN West Sumatera Campus Fauzi, Fauzi; Istijono, Bambang; Hidayat, Benny
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.8171

Abstract

The sustainable availability of clean water is crucial for supporting academic, residential, and institutional operational activities in higher education settings. In general, previous research has primarily focused on clean water planning at the city or regional level, without examining the need and availability of water on boarding campuses that have distinct consumption patterns and distribution systems. This research aims to fill the gap by conducting an integrated evaluation of water needs and availability, serving as the basis for preparing a water management master plan at the West Sumatra IPDN Campus. A mixed-methods approach is employed, combining quantitative analysis based on SNI 03-7065-2005 to estimate water needs with qualitative analysis of infrastructure conditions and water quality through field surveys, interviews, and laboratory tests. The results showed that the water demand reached 92,150 liters/day (1.1 liters per second), while the source capacity was 5.03 liters per second, resulting in a surplus of 1,839%. Although the water supply was quantitatively adequate, quality tests revealed turbidity and bacteriological contamination at some distribution points, attributed to the corrosion of galvanized pipes and the absence of secondary filtration. This confirms that sufficient quantity does not guarantee the quality and efficiency of distribution. Therefore, network modernization, the implementation of layered filtration, and periodic monitoring are necessary. This research contributes to the development of a sustainable campus water management model in Indonesia.
Predicting Bentonite Plastic Concrete Performance Using Machine Learning Fuqaha, Sameh; zaki , Ahmad
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (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.v7i1.8199

Abstract

This study develops an interpretable machine learning framework to predict the mechanical properties of bentonite plastic concrete (BPC), an essential material for low-permeability geotechnical structures. Traditional testing of BPC is time- and cost-intensive, while empirical equations often fail to capture the nonlinear effects of bentonite and curing conditions. To address these limitations, four ensemble learning models were optimized using the Forensic-Based Investigation Optimization (FBIO) algorithm, a parameter-free metaheuristic inspired by investigative search processes. The models were trained on three curated experimental datasets to predict slump, tensile strength, and elastic modules. Among all, XGB–FBIO achieved the highest accuracy for slump (R² = 0.98) and tensile strength (R² = 0.99), while GBRT–FBIO performed best for elastic modulus (R² = 0.97). SHapley Additive exPlanations (SHAP) analysis revealed curing time, cement, and water content as the most influential variables. The results demonstrate that the proposed framework can replace repetitive laboratory trials with data-driven insights, providing engineers with a reliable, explainable, and resource-efficient tool for optimizing BPC mix designs in environmental and geotechnical applications.

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