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Identification of glucose levels in urine based on classification using k-nearest neighbor algorithm method Cover

Identification of glucose levels in urine based on classification using k-nearest neighbor algorithm method

International Journal on Smart Sensing and Intelligent Systems
Volume 16 (2023): Issue 1 (January 2023)
By: Anton Yudhana,  Fathiyyah Warsino,  Son Ali Akbar,  Fatma Nuraisyah and  Ilham Mufandi  
Open Access
|Aug 2023

Authors

Anton Yudhana

eyudhana@ee.uad.ac.id

Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Indonesia

Fathiyyah Warsino

Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Indonesia

Son Ali Akbar

Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Indonesia

Fatma Nuraisyah

Public Health Science Study Program, Faculty of Public Health, Universitas Ahmad Dahlan, Indonesia

Ilham Mufandi

Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Indonesia
Department of Agro-industrial Technology, Faculty of Science and Technology, University of Darussalam Gontor, Indonesia
DOI: https://doi.org/10.2478/ijssis-2023-0006 | Journal eISSN: 1178-5608
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Language: English
Submitted on: Aug 15, 2022
Published on: Aug 3, 2023
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Glucose,
urine,
AS7262,
classification,
K-nearest neighbor
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2023 Anton Yudhana, Fathiyyah Warsino, Son Ali Akbar, Fatma Nuraisyah, Ilham Mufandi, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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