DOI : https://doi.org/10.25077/jitce.2.02.85-91.2018

Identifikasi Penyakit Diabetes Mellitus Melalui Nafas Berbasis Sensor Gas Dengan Metode Fast Fourier Transform dan Backpropagation

Mohammad Hafiz Hersyah (1), Andrizal Andrizal (2), Revinessia Revinessia (3)
(1) Universitas Andalas
(2) Politeknik Negeri padang
(3) Universitas Andalas
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How to cite (IJASEIT) :
Hersyah, M. H., Andrizal, A., & Revinessia, R. (2018). Identifikasi Penyakit Diabetes Mellitus Melalui Nafas Berbasis Sensor Gas Dengan Metode Fast Fourier Transform dan Backpropagation. JITCE (Journal of Information Technology and Computer Engineering), 2(02), 85–91. https://doi.org/10.25077/jitce.2.02.85-91.2018
Citation Format :
The purpose of this research is to detect whether a person has diabetes mellitus or not. In people with diabetes mellitus uncontrolled will result in a decline in the rate of saliva that results in bad breath. The system uses the sensor TGS 2602 and MQ 4. It's function is to detect the levels of Hydrogen Sulfide and Methan in a person’s breath. The decision is made by using the neural network with a backpropagation method. The result for 5 (five) tests of diabetes mellitus samples can be detected with a success rate of 80%, whereas using random samples, the test detected with detected with a success rate of 80% samples that didn’t contain diabetes mellitus. This system could provide a solution for testing if a person is suffering from diabetes mellitus
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