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Irza Sukmana
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INDONESIA
International Journal of Aviation Science and Engineering
Published by Institut Teknologi Bandung
ISSN : 27215342     EISSN : 27156958     DOI : https://doi.org/10.47355/avia.v1i1.6
Core Subject : Engineering,
Aerospace Engineering Automotive Engineering Electrical & Electronics Engineering Mechanical Engineering Transportation
AVIA : International Journal of Aviation Science and Engineering is published by Faculty of Mechanical and Aerospace Engineering, FTMD Institut Teknologi Bandung, Indonesia - in cooperation with Faculty of Engineering, Universitas Lampung and Java Scientific Academy, Indonesia. International Journal of Aviation Science and Engineering aims to publish original research articles and critical review manuscript in the field of Aviation Science and Engineering as well as Aerospace and applied Mechanical Engineering. The topics are including, but limited to: aviation sciences and technology, aerospace engineering, aeronautics, defense system and engineering, safety and energy, mechanical engineering, aeronautics education and training, interdisciplinary engineering and applied sciences.
Arjuna Subject : Teknik (semua kategori) - Teknik Ruang Angkasa
Articles 10 Documents
 1 
Search results for , issue "Vol. 4, No. 2 (December 2022)" : 10 Documents clear
Effect of Production Method on the Mechanical Properties of Resin - Fiber S-GLASS Composite for the Rocket Nose Cone Application Tarkono Tarkono; Sugiyanto Sugiyanto; Akhmad Riszal; Ignatius Bayu Atmoko; Fauzi Ibrahim; Joy Rizki Pangestu Djuansjah
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.v4i2.69

Abstract

Composite materials are increasingly developing in industrial advances both for everyday life or technological applications in industry. Composite material is a combination of two or more different components. Composite materials have certain physical and mechanical properties that are better than the properties of each of their constituent components. This research has been analyzed to determine the effect of the method of making fiber composites s-glass matrix resin 100 as material nose cone rocket rx-450 by using the method of hand lay up and vacuum infusion. Making a nose cone is carried out in several stages which are quite complicated, starting with preparation master mole for print beginning until polishing compound molding release on molding as finishing. The results obtained from this study are by using the method vacuum infusion lighter compared with material results method hand lay-up because on method vacuum infusion resin can be removed from the laminate. Whereas on method hand layup infiltration resin in fiber not enough perfect and administration of resin that cannot be controlled so that it can affect the mass from product composite.
Systematic Comparison of Machine Learning Model Accuracy Value Between MobileNetV2 and XCeption Architecture in Waste Classification Syste Yessi Mulyani; Rian Kurniawan; Puput Budi Wintoro; Muhammad Komarudin; Waleed Mugahed Al-Rahmi
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.v4i2.70

Abstract

Garbage generated every day can be a problem because some types of waste are difficult to decompose so they can pollute the environment. Waste that can potentially be recycled and has a selling value is inorganic waste, especially cardboard, metal, paper, glass, plastic, rubber and other waste such as product packaging. Various types of waste can be classified using machine learning models. The machine learning model used for classification of waste systems is a model with the Convolutional Neural Network (CNN) method. The selection of the CNN architecture takes into account the required accuracy and computational costs. This study aims to determine the best architecture, optimizer, and learning rate in the waste classification system. The model designed using the MobileNetV2 architecture with the SGD optimizer and a learning rate of 0.1 has an accuracy of 86.07% and the model designed using the Xception architecture with the Adam optimizer and a learning rate of 0.001 has an accuracy of 87.81%.
Bird Detection System Design at The Airport Using Artificial Intelligence Khairul Ummah; Muhammad Fadly Hidayat; Denni Kurniawan; Zulhanif Zulhanif; Javensius Sembiring
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.v4i2.72

Abstract

Bird strike is a process of crashing between bird and airplane which occurs in flight phase. Based on data, there are 40 times bird strike occurs every day (FAA, 2019). There are lot of research that already conducted to decrease number of birds at the airport. But it is not given significant changes. Hence, it is needed a model that can detect bird at the airport so that we can decrease the number of birds. Study already conducted by comparing motion detection with object detection and filter which can be used to improve detection quality. Model already developed using YOLOv4 object detection with 71.89% mean average precision. It is expected that object detection can be developed to become a bird repellent system in the future
Selection of the Use of Formwork in the Holiday Inn Bukit Randu Hotel Project Using the Fuzzy AHP Method Sc. Elan Lida Fajarviani; Kristianto Usman; Anita Lestari Condro Winarsih
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.v4i2.74

Abstract

Along with the development of the construction world, formwork has also progressed from being assembled on site to being assembled first at the factory. In Indonesia, many types of formwork have been used, which each have their own advantages and disadvantages. In selecting the type of formwork used, many factors or criteria need to be considered. The purpose of this study is to determine the type of formwork that is relatively best for use in the Holiday Inn Bukit Randu Hotel Project by calculating the weight of the criteria, sub criteria, and also the alternatives used using the Fuzzy AHP Method. Based on the criteria and alternatives that have been compiled by the researcher, as well as the analysis carried out using the Fuzzy AHP method, it is known that metal (system) formwork is the relatively best formwork with the largest final weight of 43.6%, while semi-system formwork with a final weight of 24, 6% and conventional formwork by 31.8%. However, after being reviewed based on the cost aspect, the semi-system formwork is the relatively best formwork to be used in the Holiday Inn Bukit Randu Hotel Project.
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
Effect of Production Method on the Mechanical Properties of Resin - Fiber S-GLASS Composite for the Rocket Nose Cone Application Tarkono, Tarkono; Sugiyanto, Sugiyanto; Riszal, Akhmad; Atmoko, Ignatius Bayu; Ibrahim, Fauzi; Djuansjah, Joy Rizki Pangestu
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.v4i2.69

Abstract

Composite materials are increasingly developing in industrial advances both for everyday life or technological applications in industry. Composite material is a combination of two or more different components. Composite materials have certain physical and mechanical properties that are better than the properties of each of their constituent components. This research has been analyzed to determine the effect of the method of making fiber composites s-glass matrix resin 100 as material nose cone rocket rx-450 by using the method of hand lay up and vacuum infusion. Making a nose cone is carried out in several stages which are quite complicated, starting with preparation master mole for print beginning until polishing compound molding release on molding as finishing. The results obtained from this study are by using the method vacuum infusion lighter compared with material results method hand lay-up because on method vacuum infusion resin can be removed from the laminate. Whereas on method hand layup infiltration resin in fiber not enough perfect and administration of resin that cannot be controlled so that it can affect the mass from product composite.
Systematic Comparison of Machine Learning Model Accuracy Value Between MobileNetV2 and XCeption Architecture in Waste Classification System Mulyani, Yessi; Kurniawan, Rian; Budi Wintoro, Puput; Komarudin, Muhammad; Mugahed Al-Rahmi, Waleed
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.v4i2.70

Abstract

Garbage generated every day can be a problem because some types of waste are difficult to decompose so they can pollute the environment. Waste that can potentially be recycled and has a selling value is inorganic waste, especially cardboard, metal, paper, glass, plastic, rubber and other waste such as product packaging. Various types of waste can be classified using machine learning models. The machine learning model used for classification of waste systems is a model with the Convolutional Neural Network (CNN) method. The selection of the CNN architecture takes into account the required accuracy and computational costs. This study aims to determine the best architecture, optimizer, and learning rate in the waste classification system. The model designed using the MobileNetV2 architecture with the SGD optimizer and a learning rate of 0.1 has an accuracy of 86.07% and the model designed using the Xception architecture with the Adam optimizer and a learning rate of 0.001 has an accuracy of 87.81%.
Bird Detection System Design at The Airport Using Artificial Intelligence Ummah, Khairul; Hidayat, Muhammad Fadly; Kurniawan, Denni; Zulhanif, Zulhanif; Sembiring, Javensius
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.v4i2.72

Abstract

Bird strike is a process of crashing between bird and airplane which occurs in flight phase. Based on data, there are 40 times bird strike occurs every day (FAA, 2019). There are lot of research that already conducted to decrease number of birds at the airport. But it is not given significant changes. Hence, it is needed a model that can detect bird at the airport so that we can decrease the number of birds. Study already conducted by comparing motion detection with object detection and filter which can be used to improve detection quality. Model already developed using YOLOv4 object detection with 71.89% mean average precision. It is expected that object detection can be developed to become a bird repellent system in the future
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
Selection of the Use of Formwork in the Holiday Inn Bukit Randu Hotel Project Using the Fuzzy AHP Method Fajarviani, Sc. Elan Lida; Usman, Kristianto; Winarsih, Anita Lestari Condro
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.v4i2.74

Abstract

Along with the development of the construction world, formwork has also progressed from being assembled on site to being assembled first at the factory. In Indonesia, many types of formwork have been used, which each have their own advantages and disadvantages. In selecting the type of formwork used, many factors or criteria need to be considered. The purpose of this study is to determine the type of formwork that is relatively best for use in the Holiday Inn Bukit Randu Hotel Project by calculating the weight of the criteria, sub criteria, and also the alternatives used using the Fuzzy AHP Method. Based on the criteria and alternatives that have been compiled by the researcher, as well as the analysis carried out using the Fuzzy AHP method, it is known that metal (system) formwork is the relatively best formwork with the largest final weight of 43.6%, while semi-system formwork with a final weight of 24, 6% and conventional formwork by 31.8%. However, after being reviewed based on the cost aspect, the semi-system formwork is the relatively best formwork to be used in the Holiday Inn Bukit Randu Hotel Project.

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