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Dahlan Abdullah
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International Journal of Engineering, Science and Information Technology
Published by Universitas Malikussaleh
ISSN : -     EISSN : 27752674     DOI : -
Core Subject : Science, Education, Social, Engineering,
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation
The journal covers all aspects of applied engineering, applied Science and information technology, that is: Engineering: Energy Mechanical Engineering Computing and Artificial Intelligence Applied Biosciences and Bioengineering Environmental and Sustainable Science and Technology Quantum Science and Technology Applied Physics Earth Sciences and Geography Civil Engineering Electrical, Electronics and Communications Engineering Robotics and Automation Marine Engineering Aerospace Science and Engineering Architecture Chemical & Process Structural, Geological & Mining Engineering Industrial Mechanical & Materials Science: Bioscience & Biotechnology Chemistry Food Technology Applied Biosciences and Bioengineering Environmental Health Science Mathematics Statistics Applied Physics Biology Pharmaceutical Science Information Technology: Artificial Intelligence Computer Science Computer Network Data Mining Web Language Programming E-Learning & Multimedia Information System Internet & Mobile Computing Database Data Warehouse Big Data Machine Learning Operating System Algorithm Computer Architecture Computer Security Embedded system Coud Computing Internet of Thing Robotics Computer Hardware Information System Geographical Information System Virtual Reality, Augmented Reality Multimedia Computer Vision Computer Graphics Pattern & Speech Recognition Image processing ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 673 Documents
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Design and Development of a Mini Excavator as Innovative Learning Media Abdul Tahir; Irdam Irdam; Jasman Jasman; Musakirawati Musakirawati
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1775

Abstract

The rapid advancement of mechanical and electronic engineering, particularly in heavy equipment and construction automation, requires innovative learning media that effectively bridge theoretical knowledge and practical implementation. Conventional instructional methods often provide limited opportunities for students to develop hands-on experience with complex mechatronic systems. This study presents the design, development, and evaluation of a miniature battery-electric excavator intended as an educational platform for teaching construction robotics, automation, and sustainable engineering principles. The development process followed a structured methodology consisting of conceptual design, mechanical fabrication, electronic integration, simulation, and functional testing. Unlike conventional excavators that rely on hydraulic actuators, the proposed system employs electric motors to drive the boom, arm, and bucket mechanisms, demonstrating an energy-efficient and environmentally friendly alternative. Locomotion is achieved using DC gearbox motors for wheel movement, while an independent DC motor enables 90° rotational motion. The control architecture is based on an Arduino Mega microcontroller integrated with a wireless PS2 joystick, providing intuitive and precise user control. Lightweight aluminum was selected for the backhoe assembly to reduce overall weight, whereas the main chassis was constructed from mild steel to ensure structural strength and operational stability. Experimental evaluation confirmed that the prototype successfully performed essential excavation motions, achieving a maximum horizontal reach of 1,400 mm, a vertical reach of 1,420 mm, an average operating speed of 0.5 m/s, and a maximum speed of 1.0 m/s. With compact dimensions of 800 × 600 × 750 mm, the system is safe, portable, and suitable for laboratory-based education. Furthermore, the platform supports Deep Neural Network (DNN) data generation and reinforcement learning research, providing a cost-effective and safe environment for advancing student competencies in intelligent construction technologies
Integrated Planning for Sustainable Clean Water and Sanitation at Mulawarman University Fahrizal Adnan; Febrina Zulya; Searphin Nugroho; Rahmahtriananda Faradilla; Aulia Fauziyah Luayi; Rizqi Nadhirawati; Budi Nining Widiarti; Ibrahim Ibrahim
International Journal of Engineering, Science and Information Technology Vol 6, No 1 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i1.1888

Abstract

Clean water and sanitation are essential components of a healthy, safe, and sustainable campus environment. At Mulawarman University, increasing numbers of students, lecturers, staff, and other academic community members require adequate water supply and sanitation infrastructure to support educational, administrative, and daily activities. This study aims to develop a long-term plan for clean water provision and sanitation facilities based on projected population growth through 2048. The methodology includes population projection analysis, estimation of clean water demand, assessment of sanitation facility requirements, and planning for solid and liquid waste management. The results indicate that demand for clean water and sanitation infrastructure will increase consistently with the growth of the university population. At the end of the sixth planning period in 2048, the projected served population reaches 64,458 people. This population requires a clean water production capacity of 966.88 m³/day to meet projected demand. Solid-waste management requirements include ten temporary waste-storage facilities (TPS), three dump-truck fleets, and one integrated waste-treatment facility (TPST) with an estimated required area of 1,129.38 m². Meanwhile, wastewater management must accommodate a potential black-water discharge of 96.69 m³/day and grey-water discharge of 676.81 m³/day. Based on these projections, the study recommends developing an integrated clean-water distribution network, improving solid-waste collection and treatment facilities, and establishing an integrated wastewater-management system capable of accommodating future demand. The proposed planning framework is expected to support Mulawarman University in improving environmental quality, strengthening campus sanitation services, and achieving more sustainable infrastructure development. Furthermore, the findings provide a quantitative basis for phased infrastructure investment and long-term campus environmental management through 2048
An Explainable Optimization Framework for Demand-Driven Inventory Decisions Using SHAP and Mixed Integer Programming Alfry Aristo Jansen Sinlae; Fajriana Fajriana; Yenny Suzana; Kiki Puspo Arianty
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1882

Abstract

Demand uncertainty complicates inventory decision-making and requires decision-support systems that are both accurate and transparent. However, existing studies primarily emphasize either demand forecasting or inventory optimization, with limited attention to integrating explainability into a unified decision-making framework. This study develops and evaluates an Explainable Optimization Framework that combines Extreme Gradient Boosting (XGBoost) for demand forecasting, SHapley Additive exPlanations (SHAP) for model interpretability, and Mixed Integer Programming (MIP) for inventory optimization. The framework was developed following the Design Science Research methodology, encompassing problem identification, artifact development, demonstration, evaluation, and communication. Model performance was assessed using rolling-origin backtesting to provide a robust evaluation under dynamic and uncertain demand conditions. Forecasting accuracy was measured using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). Experimental results demonstrate that XGBoost achieved the highest forecasting accuracy, with an RMSE of 43.87, MAE of 33.92, and MAPE of 7.61%. The forecasted demand was subsequently incorporated into the MIP optimization model, resulting in a 22.3% reduction in total inventory cost, an increase in service level from 91.2% to 96.8%, an improvement in fill rate from 89.7% to 95.4%, a 57.1% reduction in stockout frequency, and an increase in inventory turnover from 5.8 to 7.2 compared with the baseline approach. SHAP analysis identified historical demand, promotional activities, and product price as the most influential variables affecting demand predictions, providing transparent explanations that enhance managerial trust and support informed inventory decisions. Overall, the proposed framework demonstrates that integrating forecasting, explainability, and mathematical optimization into a unified decision pipeline significantly improves operational efficiency, inventory performance, decision transparency, and resilient data-driven supply chain management across diverse industrial sectors

Page 68 of 68 | Total Record : 673

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