Article Per Year (5 Year)
p-Index From 2021 - 2026
3.799
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Jurnal Mechanical Jurnal Ilmiah Teknik Mesin Turbo : Jurnal Program Studi Teknik Mesin Journal of Engineering and Scientific Research (JESR) International Journal of Aviation Science and Engineering Journal of Innovation and Technology Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Sains dan Teknologi Journal of Applied Science, Engineering and Technology (J. ASET) Seminar Nasional Insinyur Profesional (SNIP) Jurnal Polimesin Nemui Nyimah
A.Yudi Eka Risano
Department Of Mechanical Engineering, Faculty Of Engineering, Universitas Lampung Bandar Lampung, 35145, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

Published : 42 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : International Journal of Aviation Science and Engineering

 1 
Deep Learning Implementation on Aerial Flood Victim Detection System Khairul Ummah; M Thariq Hidayat; A Yudi Eka Risano
AVIA Vol. 4, No. 2 (December 2022)
Publisher : Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v4i2.73

Abstract

Hydrometeorological hazard such as floods are considered as a regular natural disaster in Indonesia due to its frequent occurrence. To mitigate the risk, search and rescue operations need to be carried out immediately. The sheer magnitude of floods poses a major challenge for responders, and the emerging drone technology could help to alleviate the problem due to its deployment speed and coverage. Automation in drone technology has potential to improve its effectiveness. This paper explores the idea of human detection during floods using a computer vision approach. This approach utilizes a one stage detector model as detection speed is crucial in disaster management case. The dataset used for training consists of 200 labelled and negative images taken from drone point of view. This paper conducted 3 experiments to find out the difference in performance when the model was trained on flood and non-flood dataset, as well as the effect of image input size to the model’s performance. The first experiment was trained on non-flood dataset. The second experiment was trained on flood dataset, and the third experiment is the modified version of the second model. The results show that the model trained on flood dataset performed worse than non-flood counterparts with the non-flood mAP reached 90.80% while flood mAP reached 39.15%. In addition, the experiments also conclude that increasing the input size of image during training, will increase the detection performance of the model at the cost of FPS
Deep Learning Implementation on Aerial Flood Victim Detection System Ummah, Khairul; Hidayat, M Thariq; Risano, A Yudi Eka
International Journal of Aviation Science and Engineering - AVIA Vol. 4, No. 2 (December 2022)
Publisher : FTMD Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v4i2.73

Abstract

Hydrometeorological hazard such as floods are considered as a regular natural disaster in Indonesia due to its frequent occurrence. To mitigate the risk, search and rescue operations need to be carried out immediately. The sheer magnitude of floods poses a major challenge for responders, and the emerging drone technology could help to alleviate the problem due to its deployment speed and coverage. Automation in drone technology has potential to improve its effectiveness. This paper explores the idea of human detection during floods using a computer vision approach. This approach utilizes a one stage detector model as detection speed is crucial in disaster management case. The dataset used for training consists of 200 labelled and negative images taken from drone point of view. This paper conducted 3 experiments to find out the difference in performance when the model was trained on flood and non-flood dataset, as well as the effect of image input size to the model’s performance. The first experiment was trained on non-flood dataset. The second experiment was trained on flood dataset, and the third experiment is the modified version of the second model. The results show that the model trained on flood dataset performed worse than non-flood counterparts with the non-flood mAP reached 90.80% while flood mAP reached 39.15%. In addition, the experiments also conclude that increasing the input size of image during training, will increase the detection performance of the model at the cost of FPS
Fibrin Gel Properties and Gelation Structures for Tissue Engineering Scaffold and Biomedical Engineering Applications Vadival, G N; Sukmana, Irza; Risano, A Yudi Eka; Sugiri, Agus; Hamdani, Fadil
International Journal of Aviation Science and Engineering - AVIA Vol. 5 No. 1: (June 2023)
Publisher : FTMD Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v5i1.85

Abstract

Fibrin gel is utilized in a wide range of medical applications, such as hemostatic agents, wound healing, drug delivery, cell delivery, cell differentiation, and tissue engineering. Notably, fibrin gel exhibits exceptional extensibility compared to other filamentous biopolymers, capable of stretching over five times its original length without breaking. Remarkably, it can fully recover from elongations exceeding 100% once the applied stress is removed. This paper presents an optimized formulation of fibrinogen and thrombin tailored for culturing human umbilical vein endothelial cells (HUVEC). We explore the mechanical and physical properties of the fibrin gel, aiming to identify ways to enhance its medical applications. The gel is synthesized in vitro through the combination of fibrinogen and thrombin, allowing us to assess how varying the proportions of these components affects the gel structures and properties
Co-Authors . Harmen . Sulistiyono Abdul Aziz Adi Ernadi Agus Sugiri Agus Sugiri Agus Sugiri, Agus Ahmad Riszal Ahmad Su'udi Ahmad Suudi Ahmad Suudi Akhmad Riszal Amrul Amrul Anandati, Ghea Maulidaco Andy Abdel Hakim Angga Wijaya, Angga Anwar, Hasrul Anwar, Syaipudin Ari Andrew Pane Arifin Kusumo Wicaksono Asep Sukohar Baddarudin, Mohammad Bayu, Chandra Choirul Anam Djana, Miftahul Eko Yohanes Erisha Putri Eriyadi, Riko Hamdani, Fadil Harmen Harnowo Supriadi, Harnowo Herry Wardono HERU WAHYUDI Hidayat, M Thariq Ibrahim, Fauzi Irza Sukmana Irza Sukmana Irza Sukmana Irza Sukmana Irza Sukmana, Irza Khairul Anwar Khairul Ummah Khairul Ummah Lamsihar S Tamba M Thariq Hidayat M. Dyan Susila M. Dyan Susila ES M. Haviz M. Rangga Saputra Maherariyat, Maherariyat Mahruri Arif Wicaksono Mahruri Arif Wicaksono Maulana Efendi Mayasari, Rizka Meylia Rodiawati Muhammad Badaruddin Muhammad Hanif Muhammad Irsyad Muhammad Irsyad Nafrizal Nandi Haerudin Noorhidana, Vera A Novri Tanti Novri Tanti, Novri Panji Kurniawan Paska W, Andreas Rahmat Ramadhan Renardy, B Niko Rendy Dwi A.P. Riszal, Ahmad Riszal, Akhmad Rizal Adi Saputra Rizal Adi Saputra Sandy Dwi Hardin Sari, Devi Kurnia Sihombing, Gunawan Poniton R.P. Simparmin br Ginting Subekti Bagus W SUGIYANTO Sugiyanto - Tarkono Tarkono Tebu, Yohanes Yonathan Thalya Miranda Thohirin, Muh Vadival, G N Wijaya, Riki C Yoga Pratama Zulhanif Zulhanif, Zulhanif