Optimizing urine protein detection accuracy using the K-nearest neighbors algorithm and advanced image segmentation techniques
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Authors
Anton Yudhana
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Novi Febrianti
Department of Biology, Faculty of Applied Science and Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Ilham Mufandi
Department of Agro-Industrial Technology, Faculty of Science and Technology, Universitas Darussalam Gontor, Indonesia
Arsyad Cahya Subrata
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Nuni Ihsana
Faculty of Medicine, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Son Ali Akbar
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Liya Yusrina Sabila
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Helda Pratama
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Nisa Fajriyanti
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Sri Lestari
Rumah Sakit Umum Daerah (RSUD), Purworejo, Indonesia
Ismail Rakip Karas
Department of Computer Engineering, Demir Celik Campus, Karabuk University, Karabuk, Turkey
DOI: https://doi.org/10.2478/ijssis-2025-0039 | Journal eISSN: 1178-5608
Language: English
Submitted on: Sep 14, 2024
Published on: Jul 26, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
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© 2025 Anton Yudhana, Novi Febrianti, Ilham Mufandi, Arsyad Cahya Subrata, Nuni Ihsana, Son Ali Akbar, Liya Yusrina Sabila, Helda Pratama, Nisa Fajriyanti, Sri Lestari, Ismail Rakip Karas, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.