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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL ELEKTRO ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) MITRA: Jurnal Pemberdayaan Masyarakat EPIC : Journal of Electrical Power, Instrumentation and Control Jurnal Mantik SABDAMAS Jurnal Locus Penelitian dan Pengabdian Jurnal Teknologi dan Manajemen Industri Terapan ROUTERS: Jurnal Sistem dan Teknologi Informasi Jurnal Pengabdian Masyarakat Charitas Metris: Jurnal Sains dan Teknologi Cylinder : Jurnal Ilmiah Teknik Mesin
Karel Octavianus Bachri
Program Studi Teknik Elektro, Fakultas Biosains, Teknologi Dan Inovasi, Universitas Katolik Indonesia Atma Jaya Jakarta
Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences

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Journal : telkomnika telecommunication computing electronics and control

 1 
Cognitive artificial-intelligence for doernenburg dissolved gas analysis interpretation Karel Octavianus Bachri; Umar Khayam; Bambang Anggoro Soedjarno; Arwin Datumaya Wahyudi Sumari; Adang Suwandi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.11612

Abstract

This paper proposes Cognitive Artificial Intelligence (CAI) method for Dissolved Gas Analysis (DGA) interpretation adopting Doernenburg Ratio method. CAI works based on Knowledge Growing System (KGS) principle and is capable of growing its own knowledge. Data are collected from sensors, but they are not the information itself, and thus, data needs to be processed to extract information. Multiple information are then fused in order to obtain new information with Degree of Certainty (DoC). The new information is used to identify faults occurred at a single observation. The proposed method is tested using the previously published dataset and compared with Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Experiment shows CAI implementation on Doernenburg Ratio performs 115 out of 117 accurate identification, followed by Fuzzy Inference System 94.02% and ANN 78.6%. CAI works well even with small amount of data and does not require trainings.
Tomato leaf disease recognition system using Faster R-CNN Karel Octavianus Bachri; Bryan Santoso; Duma Kristina Yanti Hutapea; Catherine Olivia Sereati; Lanny W. Pandjaitan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.25519

Abstract

The objective of this paper is to detect tomato leaf disease using Faster region-based convolutional neural network (R-CNN). The tomato leaf disease recognition system utilizes a dataset consisting of healthy tomato leaves and eight leaf diseases, including early blight, late blight, leaf mold, mosaic virus, septoria, spider mites, yellow leaf curl virus, and leaf miner. The dataset is obtained from various sources, such as Kaggle, Google Images, Bing Images, and Roboflow Universe. Pre-processing techniques, including collage, tile, static crop, and resize, are applied to prepare the dataset for training. Data augmentation methods, such as flipping, 90° rotation, exposure adjustment, and hue modification, are applied to enhance the model’s robustness and generalize its performance. Specifically, we implemented Faster R-CNN as part of Detectron2 using its base models and configurations. The results demonstrate that the X101-FPN base model for Faster R-CNN with the default configurations of Detectron2 is efficient and general enough to be applied to defect detection. This approach results in an average precision (AP) detection score of 87.01% for validation results.
Co-Authors Adang Suwandi Ahmad Agi Tama Agi Tama Alexander, Justin Alvinson, Gregorius Andre Sugioko Anthon de Fretes Anthony , Jean Arka Dwinanda Soewono Arwin Datumaya Wahyudi Sumari Bambang Anggoro Soedjarno Bambang Iwan Suryana Bryan Santoso Bunardi, Marcelinus Eric Catherine Olivia Sereati Christine Natalia Duma Kristina Yanti Duma Kristina Yanti Hutapea Enny Widawati Erik Agustian Yulanda Fernanto, Nico Ferry Rippun Gideon Manalu, Ferry Rippun Gideon FLORENTIA ANGELINA Fortino, Antonius Edwin Hadikusuma, Ridwan Satrio Herianto, David Hidayat, Renaldi Irpan Restu Ade Putra Joko Tri Susilo Jonathan, Edoardo Karangga, Yusaphat Phosa Kartadinata, Budi Kelvin, Dimas Kevin Kevin kevin Khayam, Umar Kusmanto, Willy Lanny W Lanny W. Pandjaitan Lestari, Hesti Tri Linda Wijayanti Lukas Maria Angela Kartawidjaja Marsellinus Bachtiar Wahju Marsul Siregar Marten Darmawan Melisa Mulyadi Micha Thesania Katarine Michael Deni Perdana Putera Muhamad Jaelani Sidik Muhammad Risqi Nuryana Nabil, Alfi Nova Eka Budiyanta Osmond, Edbert Pandjaitan, Lanny W. Pangestu, Devin PANJAITAN, LANNY Pardosi, Cristoni Hasiholan Pascalis Paschalis, Sebastian Michael Paskalis, Yohanes Maria Jonathan Glenn PRAWIRA, WASKITO Putera, Michael Deni Perdana PUTRA, SADIANA Rippun G. Manalu, Ferry Rizki Surya Permana Rory Anthony Hutagalung Sachi, Haenuki Sandra Octaviani B. Widiarto Satryanatha, Josaphat Febrian Setiawan, Axel Gilbert Soewono, Arka Soewono, Arka D. Surya Permana, Rizky Surya Widjaja, Williem Sutomo, Febryan Tajuddin Nur Theresia Ghozali Timothy Sutjipto, Marcellus Timothy Wijaya, Hans Tobias Mikha Sulistiyo Trifenaus Prabu Hidayat Veronica Windha Mahyastuty Widodo Basuki Widodo Widjaja Basuki Wijaya, Nickolas Dario Wijaya, Toby Wilson Yudha Harnoko Zefanya, Maria