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p-Index From 2021 - 2026
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All Journal International Journal of Basic and Applied Science Andalasian International Journal of Applied Science, Engineering, and Technology
Muhammad Ilhamdi Rusydi
Universitas Andalas, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Mechanical Engineering Physics

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Electrooculography Based Control of a Robotic Manipulator with Dual Cameras for Object Retrieval Muhammad Ilhamdi Rusydi; Andre Paskah Gultom; Adam Jordan; Rahmad Novan Nurhadi; Darwison Darwison
International Journal of Basic and Applied Science Vol. 14 No. 4 (2026): March: Computer Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i4.798

Abstract

This study presents an assistive control system for a four-degree-of-freedom (4-DoF) robotic manipulator that integrates image-based spatial perception with electrooculography (EOG)-based human–machine interaction for three-dimensional object retrieval. The system is motivated by the need for intuitive, non-contact assistive technologies to support individuals with severe motor impairments, such as tetraplegia, in performing basic manipulation tasks. The proposed framework employs an orthogonal dual-camera vision configuration to achieve explicit 3D target localization, where planar object positions on the XY plane and depth along the Z axis are estimated using focal length–based geometric modeling. User commands are generated through an EOG interface, in which eye movements and voluntary blinks are classified using a K-Nearest Neighbor (KNN) algorithm to control manipulator motion. Compared to conventional assistive robotic systems that rely on depth sensors or high-degree-of-freedom manipulators, the proposed approach utilizes asymmetric monocular viewpoints and a minimal 4-DoF architecture to reduce system complexity. Experimental results demonstrate high performance, achieving average localization accuracies of 99.52% on the XY plane and 95.88% along the Z axis, as well as an EOG classification accuracy of 94.38%. Manipulation experiments confirmed reliable operation with a 100% task success rate, while task completion time and positional error increased gradually with target distance. These findings validate the feasibility of the proposed system as a low-complexity, high-accuracy assistive robotic solution for rehabilitation and human–machine interaction applications.
Development of Electrical Laboratory Information System using Model View Controller Architecture Zen Resti Maulana; Eka Fitrianto; Muhammad Ilhamdi Rusydi; Asrul Azani Mahmood
Andalasian International Journal of Applied Science, Engineering and Technology Vol. 6 No. 1 (2026): March 2026
Publisher : LPPM Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/aijaset.v6i1.319

Abstract

Effective and efficient laboratory inventory management is crucial to support academic and research activities in higher education. The manual system currently used to manage eight laboratories in the electrical engineering department often leads to various problems, such as recording errors, asset loss, and inaccuracy in reporting. This is the urgency of establishing an integrated information system to improve the accuracy and efficiency of laboratory inventory management. This research aims to digitize the laboratory inventory through the implementation of an application-based laboratory inventory management information system, namely Silab Elektro. In addition, this system also aims to increase transparency and accountability in laboratory asset management. This information system was developed using UML (Unified Modeling Language) modeling with MVC (Model-View-Controller) architecture. This research produces a laboratory information system that can manage equipment inventory more effectively and efficiently, as well as improve data accuracy.
Co-Authors Adam Jordan Andre Paskah Gultom Asrul Azani Mahmood Darwison Darwison Eka Fitrianto Rahmad Novan Nurhadi Zen Resti Maulana