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Applicationof Computer Visionfor Polishing RobotinAutomotive Manufacturing Industries Besari, Adnan Rachmat Anom; Zamri, Ruzaidi; Palil, Md. Dan Md.; Prabuwono, Anton Satria
EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

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

Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout partâs surface. In order to reduce the polishing time and cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper studies about vision system to measure surface defects that have been characterized to some level of surface roughness. The surface defects data have learned using artificial neural networks to give a decision in order to move the actuator of arm robot. Force and rotation time have chosen as output parameters of artificial neural networks. Results shows that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects characterization using vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotic, especially in polishing process.Keywords: polishing robot, vision sensor, surface defects, and artificial neural networks

Applicationof Computer Visionfor Polishing RobotinAutomotive Manufacturing Industries Besari, Adnan Rachmat Anom; Zamri, Ruzaidi; Palil, Md. Dan Md.; Prabuwono, Anton Satria
EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v2i2.22

Polishing is a highly skilled manufacturing process with a lot of constraints and interaction with environment. In general, the purpose of polishing is to get the uniform surface roughness distributed evenly throughout partâs surface. In order to reduce the polishing time and cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper studies about vision system to measure surface defects that have been characterized to some level of surface roughness. The surface defects data have learned using artificial neural networks to give a decision in order to move the actuator of arm robot. Force and rotation time have chosen as output parameters of artificial neural networks. Results shows that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects characterization using vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotic, especially in polishing process.Keywords: polishing robot, vision sensor, surface defects, and artificial neural networks

User Acceptance for Multitask IoT Monitoring and Controlling System for Salt Ponds Yudantoro, Tri Raharjo; Hamida, Busra Nur; Febriyanti, Eka; Wiktasari, Wiktasari; Pernanda, Suko Tyas; Prabuwono, Anton Satria
Indonesian Journal of Information Systems Vol. 6 No. 1 (2023): August 2023
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i1.7479

The process of making salt is still done manually by filling water into reservoirs and plots which require salt farmers to visit their farms periodically. This is mainly because the speed of the salt crystalization process is always inconsistent due to salt concentration in seawater and the weather. This study aims to build a new prototype of a water level monitoring system in reservoirs and plots in salt ponds then measure the water's salinity value, which will be reported to the farmers. The method used in this research is prototyping, which includes system requirement analysis, rapid design, prototype building, system evaluation, and system improvement. The system was tested using the black box method, namely testing all system functionality and determining user satisfaction with questionnaires. The functionality test results, including monitoring the water level and the pump control, show that the prototype functions correctly. The designed system can send information in the form of water level values in reservoirs, water levels in plots, and salinity values with linear sensor accuracy with measurement results with conventional measuring instruments with standard error values of 0.485, 0.44, and 0.72, respectively. Applying this system will ease farmers’ monitoring of water levels and controlling irrigation in reservoirs and plots.

High-Accuracy Stroke Detection System Using a CBAM-ResNet18 Deep Learning Model on Brain CT Images Tahyudin, Imam; Isnanto, R Rizal; Prabuwono, Anton Satria; Hariguna, Taqwa; Winarto, Eko; Nazwan, Nazwan; Tikaningsih, Ades; Lestari, Puji; Rozak, Rofik Abdul
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.569

Stroke is a brain dysfunction that occurs suddenly as a result of local or overarching damage to the brain, lasts for at least 24 hours, and causes about 15 million deaths each year globally. Immediate medical treatment is essential to reduce the potential for further brain damage in stroke patients. Medical imaging, especially computed tomography (CT scan), plays a crucial role in the diagnosis of stroke. This study aims to develop and evaluate a deep learning architecture based on Convolutional Block Attention Module (CBAM) and ResNet18 for stroke classification in CT images. This model is designed through data preprocessing, training, and evaluation stages using a cross-validation approach. The results showed that the CBAM-ResNet18 integration resulted in a high accuracy of 95% in distinguishing stroke and non-stroke cases. The accuracy rate reached 96% for nonstroke identification (class 0) and 94% for stroke (class 1), with recall rates of 96% and 93%, respectively. Outstanding classification ability is demonstrated by an Area Under the Curve (AUC) value of 0.99. In comparison, the standard ResNet18 model shows significant fluctuations in validation loss and difficulty in generalization, with training accuracy only reaching 64-68%. On the other hand, CBAM-ResNet18 showed a significant performance improvement with a validation accuracy of 95%, a validation loss of 0.0888, and good generalization on new data. However, the limitations of the dataset and the interpretation of the results indicate the need for further validation to ensure the generalization of the model. These results show the great potential of the CBAM-ResNet18 architecture as an innovative tool in stroke diagnostic technology based on CT imaging analysis. This technology can support faster and more accurate clinical decision-making, as well as open up opportunities for further research related to the development of artificial intelligence-based systems in the medical field.

Islamic Economic Perspectives on Global Economic Integration: A Theoretical Framework Putri, Nurul Wulandari; Prabuwono, Anton Satria
Jurnal Internasional Ekonomi Islam Vol 7 No 01 (2025): International Journal of Islamic Economics
Publisher : The Postgraduate of Institut Agama Islam Negeri Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32332/ijie.v7i01.10302

Introduction: Globalization certainly has a significant impact on the lives of Indonesian people. This impact includes two aspects, namely positive and negative. The influence of globalization has also penetrated all areas of life, including politics, economics, thought, and socio-cultural life. With its concept of Sharia economics, Islam is present at the right time and is warmly welcomed by the community. Islamic economics seems to be at least considered an alternative answer to the chaos of economic globalization. Objective: This study examines whether Islamic Economics can be an alternative answer to the increasingly complex chaos of economic globalization. Method: This study uses Library Research, commonly called a literature review. The data is obtained from various related literature, which is classified and analysed using a critical philosophical approach. Result: The results show that the concept of Islamic economics aims to achieve Maqasid Shari'ah, which includes the fulfilment of five basic needs (al-ḍaruriyat al-khams), namely the protection of religion, soul, mind, offspring, and property. To achieve this goal, steps that need to be taken include revitalization of the human element, reduction of wealth concentration, economic restructuring, and fiscal restructuring. Implication: This research provides an understanding that Islamic economics has the potential to be an effective alternative in dealing with the inequalities and challenges posed by the global economy.

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