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All Journal Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat Jurnal Teknologi Elekterika
Arief, Ardiaty
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Public Health

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Performance Improvement of Deep Convolutional Networks for Aerial Imagery Segmentation of Natural Disaster-Affected Areas Nugraha, Deny Wiria; Ilham, Amil Ahmad; Achmad, Andani; Arief, Ardiaty
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1383

Abstract

This study proposes a framework for improving performance and exploring the application of Deep Convolutional Networks (DCN) using the best parameters and criteria to accurately produce aerial imagery semantic segmentation of natural disaster-affected areas. This study utilizes two models: U-Net and Pyramid Scene Parsing Network (PSPNet). Extensive study results show that the Grid Search algorithm can improve the performance of the two models used, whereas previous research has not used the Grid Search algorithm to improve performance in aerial imagery segmentation of natural disaster-affected areas. The Grid Search algorithm performs parameter tuning on DCN, data augmentation criteria tuning, and dataset criteria tuning for pre-training. The most optimal DCN model is shown by PSPNet (152) (bpc), using the best parameters and criteria, with a mean Intersection over Union (mIoU) of 83.34%, a significant mIoU increase of 43.09% compared to using only the default parameters and criteria (baselines). The validation results using the k-fold cross-validation method on the most optimal DCN model produced an average accuracy of 99.04%. PSPNet(152) (bpc) can detect and identify various objects with irregular shapes and sizes, can detect and identify various important objects affected by natural disasters such as flooded buildings and roads, and can detect and identify objects with small shapes such as vehicles and pools, which are the most challenging task for semantic segmentation network models. This study also shows that increasing the network layers in the PSPNet-(18, 34, 50, 101, 152) model, which uses the best parameters and criteria, improves the model's performance. The results of this study indicate the need to utilize a special dataset from aerial imagery originating from the Unmanned Aerial Vehicle (UAV) during the pre-training stage for transfer learning to improve DCN performance for further research.
Perakitan Sistem WECG IoT dan Diseminasi Unjuk Kinerja untuk Memperkuat Sistem Layanan Kesehatan Puskesmas Kitta, Ikhlas; Palantei, Elyas; Suyuti, Ansar; Manjang, Salama; Samman, Faizal Arya; Nappu, Muhammad Bahtiar; Arief, Ardiaty; Said, Sri Mawar; ., Gassing; Gunadin, Indar Chaerah; ., Hasniaty; Adil, Andi Eri Andika; Palantei, Idris
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 8 No 1 (2025): Community Empowerment through Higher Education Community Service Programs
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v8i1.555

Abstract

This community service program is focused on a number of issues such as the implementation of the wireless ECG device design and the dissemination and demonstration of its technical operations in a such manner to all participants, e.g. the activists and supporters of the sub-village community healthcare center (PUSTU) located in Malimongeng Village, Salomekko District, Bone Regency. Several models of the latest WECG devices and the latest innovations have been developed and produced independently on the UNHAS campus, both hardware and software components. This Electrocardiogram (ECG) functions to monitor the condition of heart health and blood pressure in each patient who has been fitted with an ECG device. Each wireless ECG device is connected by an internet network and integrated at once in 1 Website that displays ECG signal graphics so that it can be monitored and controlled in real time from a distance. The application of ECG is very necessary for nurses or medical teams in a health institution to facilitate the control of the condition of patients in the room without having to walk back and forth to check the condition of patients being treated. The implementation of this community service is divided into 2 stages, namely the dissemination stage of basic knowledge of ECG technology and the technical training stage for operating ECG devices to support the patient condition control system at the health center. The results of recording the level of knowledge and understanding of the Malimongeng Village community who participated in community service activities carried out by a team of researchers and inventors from the Department of Electrical Engineering, Faculty of Engineering, Hasanuddin University were documented using the Googleform questionnaire application which had been designed earlier before the implementation of the activity in such a way as to measure the level of success of the implementation of the 2024 PKM program. The questionnaire survey was distributed and filled out by PKM participants online, both before and after the provision of material. After the implementation of the dissemination agenda and demonstration of the operation of the IoT WECG technology device, there was an increase in the knowledge and general understanding of the Malimongeng Village community who participated in the LBE Excellent Collaboration community service program in 2024 in both aspects of the category, namely general knowledge of health science and technical matters related to the development and production of IoT WECG devices along with their direct application in the midst of community life. The influence of participation in the series of PKM activities on both aspects of the target of counseling/socialization resulted in an increase in the capacity of knowledge in the community, namely around 30 percent and 25 percent respectively. Aspects of Technology Benefits and Activities, Based on the recommendations and input of all PKM activity participants, the following issues are highly expected by the Malimongeng Village community, including: aspects of the quality and diversity of cutting-edge science should be formulated to be more interesting and increase the insight of the village community, aspects of the availability of more sophisticated health devices should and should be equipped as soon as possible with more sophisticated and modern health infrastructure and facilities in the village and aspects of sustainability of research and development and production to overcome the problem of the availability of health facilities in the village and nationally.
Transformers for aerial images semantic segmentation of natural disaster-impacted areas in natural disaster assessment Wiria Nugraha, Deny; Ahmad Ilham, Amil; Achmad, Andani; Arief, Ardiaty
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8454

Abstract

Aerial image segmentation of natural disaster-impacted areas and detailed and automatic natural disaster assessment are the main focus of this study. Detecting and recognizing objects on aerial images of areas impacted by natural disasters and assessing natural disaster-impacted areas are still difficult problems. To solve these problems, this study utilizes four of the latest transformer-based semantic segmentation network models, bidirectional encoder representation from image transformers (BEIT), dense prediction transformer (DPT), OneFormer, and SegFormer, and proposes a detailed and automatic natural disaster assessment of the segmented image. The SegFormer model achieved the first-best result, and the OneFormer model achieved the second-best result. The SegFormer model outperformed OneFormer by 1.58% higher for the mean accuracy value and 4.28% for the mean intersection over union (mIoU) value. All receiver operating characteristics (ROC) curves have mean area under curve (AUC) values above 0.9, which means that the SegFormer model performs well in generating semantic segmentation images. The fuzzy c-means (FCM) clustering algorithm performed well and could automatically cluster the natural disaster assessments into four categories. This study has produced semantic segmentation of aerial images of areas impacted by natural disasters and natural disaster assessments, which can be used in natural disaster management systems.
The Optimal Integration of Photovoltaic (PV) and Battery Energy Storage Systems in Power Distribution Using Hybrid Flower Pollination and β-Hill Climbing ramadan, m.sahrul; Ihlas, Ihlas; Assalam, Imam Faried; Asri, Andarini; Arief, Ardiaty; Nappu, Muhammad Bachtiar
Jurnal Teknologi Elekterika Vol. 22 No. 2 (2025): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v22i2.5805

Abstract

This study discusses the optimization of the placement and capacity of Photovoltaic (PV) and Battery Energy Storage System (BESS) units in the IEEE 33-bus distribution system using the Hybrid Flower Pollination Algorithm (FPA) and β-Hill Climbing (βHC) or HyFPAβHC methods. The primary objective of this research is to enhance the performance of the distribution system by reducing power losses and improving the voltage profile. Based on the optimization results, three PV units with capacities of 749.3 kW, 577.5 kW and 620 kW were optimally placed at buses 8, 13 and 20, respectively, while one BESS unit with a capacity of 1112.4 kW was installed at bus 24. Simulation results indicate that the integration of PV and BESS significantly reduces the total system power losses from approximately 50 kW on several main feeders under the base condition (without Distributed Generation) to below 5 kW after optimization. In addition, the voltage profile improved from a minimum value of 0.92 p.u. to a stable range of 0.98–1.0 p.u. Furthermore, the integration of PV and BESS contributes to mitigating power fluctuations, enhancing energy efficiency, and improving the reliability of the distribution system operation. Therefore, the HyFPAβHC method is proven to be effective in determining the optimal configuration of PV and BESS units to improve the technical performance of electrical distribution systems.
Co-Authors Adil, Andi Eri Andika Ahmad Ilham, Amil Amil Ahmad Ilham Andani Achmad Ansar Suyuti asri, andarini Assalam, Imam Faried Deny Wiria Nugraha Faizal Arya Samman Gassing . Gunadin, Indar Chaerah Hasniaty Ihlas, Ihlas Ikhlas Kitta Nappu, Muhammad Bachtiar Nappu, Muhammad Bahtiar Palantei, Elyas Palantei, Idris ramadan, m.sahrul Salama Manjang Sri Mawar Said