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Journal : EMITTER International Journal of Engineering Technology

Classification Method in Fault Diagnosis of Oil-Immersed Power Transformers by Considering Dissolved Gas Analysis Rosmaliati; Bernandus Anggo Seno Aji; Isa Hafidz; Ardyono Priyadi; Mauridhi Hery Purnomo
EMITTER International Journal of Engineering Technology Vol 10 No 2 (2022)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v10i2.702

Abstract

Fault detection in the incipient stage is necessary to avoid hazardous operating conditions and reduce outage rates in transformers. Fault-detected dissolved gas analysis is widely used to detect incipient faults in oil-immersed transformers. This paper proposes fault diagnosis transformers using an artificial neural network based on classification techniques. Data on the condition of transformer oil is assessed for dissolved gas analysis to measure the dissolved gas concentration in the transformer oil. This type of disturbance can affect the gas concentration in the transformer oil. Fault diagnosis is implemented, and fault reference is provided. The result of the NN method is more accurate than the Tree and Random Forest method, with CA and AUC values 0.800 and 0.913. This classification approach is expected to help fault diagnostics in power transformers.
Modified Deep Pattern Classifier on Indonesian Traditional Dance Spatio-Temporal Data Mulyanto, Edy; Yuniarno, Eko Mulyanto; Hafidz, Isa; Budiyanta, Nova Eka; Priyadi, Ardyono; Hery Purnomo, Mauridhi
EMITTER International Journal of Engineering Technology Vol 11 No 2 (2023)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v11i2.832

Abstract

Traditional dances, like those of Indonesia, have complex and unique patterns requiring accurate cultural preservation and documentation classification. However, traditional dance classification methods often rely on manual analysis and subjective judgment, which leads to inconsistencies and limitations. This research explores a modified deep pattern classifier of traditional dance movements in videos, including Gambyong, Remo, and Topeng, using a Convolutional Neural Network (CNN). Evaluation model's performance using a testing spatio-temporal dataset in Indonesian traditional dance videos is performed. The videos are processed through frame-level segmentation, enabling the CNN to capture nuances in posture, footwork, and facial expressions exhibited by dancers. Then, the obtained confusion matrix enables the calculation of performance metrics such as accuracy, precision, sensitivity, and F1-score. The results showcase a high accuracy of 97.5%, indicating the reliable classification of the dataset. Furthermore, future research directions are suggested, including investigating advanced CNN architectures, incorporating temporal information through recurrent neural networks, exploring transfer learning techniques, and integrating user feedback for iterative refinement of the model. The proposed method has the potential to advance dance analysis and find applications in dance education, choreography, and cultural preservation.
Improving 3D Human Pose Orientation Recognition Through Weight-Voxel Features And 3D CNNs Riansyah, Moch. Iskandar; Putra, Oddy Virgantara; Rahmanti, Farah Zakiyah; Priyadi, Ardyono; Wulandari, Diah Puspito; Sardjono, Tri Arief; Yuniarno, Eko Mulyanto; Hery Purnomo, Mauridhi
EMITTER International Journal of Engineering Technology Vol 13 No 1 (2025)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v13i1.847

Abstract

Preprocessing is a widely used process in deep learning applications, and it has been applied in both 2D and 3D computer vision applications. In this research, we propose a preprocessing technique involving weighting to enhance classification performance, incorporated with a 3D CNN architecture. Unlike regular voxel preprocessing, which uses a zero-one (binary) approach, adding weighting incorporates stronger structural information into the voxels. This method is tested with 3D data represented in the form of voxels, followed by weighting preprocessing before entering the core 3D CNN architecture. We evaluate our approach using both public datasets, such as the KITTI dataset, and self-collected 3D human orientation data with four classes. Subsequently, we tested it with five 3D CNN architectures, including VGG16, ResNet50, ResNet50v2, DenseNet121, and VoxNet. Based on experiments conducted with this data, preprocessing with the 3D VGG16 architecture, among the five architectures tested, demonstrates an improvement in accuracy and a reduction in errors in 3D human orientation classification compared to using no preprocessing or other preprocessing methods on the 3D voxel data. The results show that the accuracy and loss in 3D object classification exhibit superior performance compared to specific preprocessing methods, such as binary processing within each voxel.
Co-Authors A.A Ngurah Amrita Adhi Kusmantoro Adi Soeprijanto Adi Soepriyanto Akbar Swandaru Almira Atha Nurhasyimi Almira Atha Nurhasyimi Anam, Sjamsul Andi Setiawan Andi Setiawan Aprilia Rahmayanti Aprilia Rahmayanti Aqsa Izza Mahendra, Rafin Arief Riambodo Ariq Arsya Nanda Arwindra Rizqiawan Asadulloh, Latief Ni'am Bernandus Anggo Seno Aji Bima Mustaqim Budiharto, Vita Lystianingrum Chandra Agung Ramadhan Daya Juang Mahaputra Diah Puspito Wulandari Dimas Anton Asfani Dimas Fajar Uman Putra Dimas Fajar Uman Putra Eko Mulyanto Yuniarno Erhankana Ardiana Putra Erlan Fajar Prihatama Fahmi Nurfaishal Farah Zakiyah Rahmanti Fath, Nifty Fauzan Fakhrul Arifin Fauzan Fakhrul Arifin Fauzan Nusyura Feby Agung Pamuji Feby Agung Pamuji Gita Dwipermata Sari Gladi Samodra Hafiz Ichwanto Hafiz Ichwanto Hannan Fatoni Hery Purnomo Heryanto Hartra M M Heryanto Hartra M M I Made Yulistya Negara IBG Manuaba Imam Abadi Imam Robandi Irrine Budi Sulistiawati Isa Hafidz Iyyaya Fariha, Nazila Jaelani Putra, Riko Satrya Fajar Januarestu, Achmad Jawahir Jumaras Situngkir Laksana, Eka Purwa Lie Jasa Lystianingrum, Vita Margo Pujiantara Mauridhi Hery P Mauridhi Hery Purnomo Mauridhi Hery Purnomo Mauridhy Hery Purnomo Moch. Iskandar Riansyah Mulyanto, Edy Nazila Iyyaya Fariha Nazila Iyyaya Fariha Nova Eka Budiyanta Nurio Herlambang Oddy Virgantara Putra Ontoseno Penangsang P., Mauridhi Hery Panji Setyo Suharso Prestian Rindho Saputra Pujiantara, Margo Pujiantoro, Margo Puspita Sari, Talitha Rachma Prilian Eviningsih Rafin Aqsa Izza Mahendra Rafin Aqsa Izza Mahendra Rakaditra Astungkara Ratna Ika Putri Rezi Delfianti Riambodo, Arief Risqiya Maulana Rizky Fadhli Hasben Rony Seto Wibowo Rosmaliati, Rosmaliati Rukmana, Maman Sandy, Yusdiar Sirait, Rummi Santi Rama Sitorus, Philip Nathanael Erlangga Sjamsjul Anam Soedibyo Soedibyo Soedibyo Soedibyo Suharto Suharto Sujono Sujono Sujono Talitha Puspita Sari Talitha Puspita Sari Talitha Puspita Sari Talitha Puspita Sari Talitha Puspita Sari Talitha Puspita Sari Talitha Puspita Sari Tegar Iman Ababil Tegar Iman Ababil Tri Arief Sardjono Tri Desmana Rachmildha, Tri Desmana Trihastuti Agustinah Vita Lystianingrum Vita Lystianingrum Wisbar, Andi Hidayah Yani Prabowo Yogadipha Bagas, I Gede Dyotha