Sistem Identifikasi Penyakit Gagal Ginjal melalui Bau Mulut, Warna Urine dan Tekanan Darah dengan Metode Support Vector Machine - Lia Safitri; Rizal Maulana; Eko Setiawan (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
The human body has a pair of kidneys that are shaped like the seed of a pea. Although it has a shape that is not so big, the kidneys have some crucial function in the human body. One of the functions of the kidneys is detoxification, which is removing metaboic waste that will become toxic if not removed from the body. One of the diseases that can attack the kidneys is kidney failure. Kidney failure is a condition when the kidneys cannot perform their functions and work properly. Kidney health should not be underestimated, then we need a system that can identify kidney conditions as early as possible to anticipate kidney damage in the human body. In this study, there are three parameters used to determine whether the kidneys are in normal condition or have kidney failure. First. To calculate the level of ammonia gas from bad breath with the MQ-135 sensor. Second, to calculated the RGB value of urine color using TCS3200 sensor and thridly, to measure blood pressure using the MPX5700AP sensor. These three parameters were choosen because they can beidentified using sensors. The data processing system in this system uses Arduino Uno. In addition, the selected classification method is support vector machine (SVM). After testing 10 times on 20 input training data. The level of accuracy of the test that have been done is 80% and the average computation time required is around 37.10 second.