Implementasi Metode K-Nearest Neighbor untuk Sistem Deteksi Covid-19 berdasarkan Suhu Tubuh dan Kadar Oksigen - Graciella Fiona Br. Panjaitan; Edita Rosana Widasari; Dahnial Syauqy (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2023)
Covid-19 disease is a contagious disease, so it is necessary to avoid direct contact between humans to minimize exposure to this virus. Examination to the hospital can allow people to be exposed to the Covid-19 virus because direct contact with some people is still carried out in an invasive way. So research is needed to detect the symptoms of Covid-19 non-invasively and does not require a lot of money and time. In this study the detection of body temperature used the MLX90614 sensor by facing the hand towards the front of the sensor so that the body temperature value was obtained. To detect oxygen levels using the MAX30100 sensor by placing your index finger on the sensor then waiting until the oxygen level value is obtained. The two values ​​from the sensor readings will be classified using the K-NN method. The output will be displayed on the LCD in the form of sensor measuring value text and classification results. The test results in this study obtained the accuracy of the sensors used. For measuring body temperature using the MLX90614 sensor, an accuracy of 99.56% was obtained, then for measuring oxygen levels using the MAX30100 sensor, an accuracy of 98.77% was obtained. In the classification test, it is determined by three distances k, namely k=3, k=5, and k=7, where k=3 gets an accuracy of 100%, k=5 gets an accuracy of 90%, and k=7 gets an accuracy of 80%. and from this classification, the average computation time is 2.38 ms.