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p-Index From 2020 - 2025
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This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Information Systems and Informatics International Journal of Applied Research and Sustainable Sciences (IJARSS)
Yusuf, Rahadian
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Religion Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Effect of dataset distribution on automatic road extraction in very high-resolution orthophoto using DeepLab V3+ Sussi, Sussi; Husni, Emir; Siburian, Arthur; Yusuf, Rahadian; Budi Harto, Agung; Suwardhi, Deni
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1650-1657

Abstract

Road extraction is one of the stages in the map-making process, which has been done manually, takes a long time, and costs a lot. Deep Learning is used to speed up the road extraction process by performing binary semantic segmentation on the image. We propose DeepLab V3+ to produce road extraction from very high-resolution orthophoto for Indonesia study area, which poses many challenges, such as road obstruction by trees, clouds, building shadows, dense traffic, and similarities to rivers and rice fields. We compared the distribution of datasets to obtain the optimal performance of the DeepLab V3+ model in relation to the dataset. The results showed that dataset ratio of 75:10:15 resulted in mean Intersection Over Union (mIoU) of 0.92 and Dice Loss of 0.042. Visually, the results of road extraction are more accurate when compared to the results obtained from different distributions of the dataset.
Heap Optimization in A* Pathfinding for Horror Games Putra, Risaldi Angga Buana; Prihatmanto, Ary Setijadi; Yusuf, Rahadian; Sukoco, Agus
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.941

Abstract

This paper examines the implementation of the A* pathfinding algorithm with binary heap optimization in a horror game environment. The horror genre in gaming uniquely engages players by placing them at the center of fear-driven experiences, where intelligent and unpredictable enemy behavior is critical for immersion. To achieve this, adaptive AI—specifically for apparitions or monsters—is controlled using A*, an algorithm renowned for its efficiency in determining the shortest path. Heap optimization is introduced to enhance A* performance by reducing the time required to identify the lowest-cost node in the Open List. Experimental results from a Unity-based prototype demonstrate that the optimized A* achieves an average pathfinding time of 1.6 ms, compared to 3.16 ms without optimization—representing a 49.37% improvement. This speed increase allows for faster and more responsive enemy behavior, resulting in heightened difficulty and more dynamic, fear-inducing gameplay. The findings highlight the potential of algorithmic optimization to significantly enhance both technical performance and player immersion in horror game design.
Conceptual Model of Architecture of 4-Layer Smart System for Emergency Response system of Negative Interaction of Human to Elephant sukoco, Agus; Prihatmanto, Ary Setijadi; Yusuf, Rahadian; Arief, Harnios; Putro, Haryanto R
International Journal of Applied Research and Sustainable Sciences Vol. 2 No. 12 (2024): December 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The interaction between elephants and humans in the era of smart systems requires a new approach to managing frequent conflicts. In this context, the development of an emergency response system based on smart system technology is very important, both for local communities and national park managers. This system is expected to utilize technology to improve the effectiveness of handling elephant emergencies. This study emphasizes the need to develop an emergency response system based on smart systems to improve the effectiveness of managing elephant-human interactions. Sustainable and participatory system development will be key to creating better solutions to these conflicts in the future.
Co-Authors Agung Budi Harto, Agung Agus Sukoco Ary Setijadi Prihatmanto Deni Suwardhi Emir Husni, Emir Harnios Arief Putra, Risaldi Angga Buana Putro, Haryanto R Siburian, Arthur Sussi