Sistem Pendeteksi Penyakit Sinusitis berdasarkan Kondisi Ingus dan Suhu Tubuh menggunakan Support Vector Machine (SVM) - Bagas Nur Rahman; Rizal Maulana; Fitri Utaminingrum (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2022)
The nose is an important organ in life for humans. In the nose there is a disease that causes the sinus wall to experience inflammation commonly known as sinusitis. Smoking habits, environmental pollution and cold air become other factors that can affect the onset of sinusitis. If sinusitis is not immediately treated and treated properly, it can lead to complications which then lead to infection. So it is necessary to do an initial check to detect sinusitis using Magnetic Resonance Imaging (MRI). In addition, the cost is quite expensive and a long period of time is the basis of this research. Therefore, a tool is needed that can detect sinusitis early. This research will use the MLX90614 sensor for body temperature feature extraction and the TCS3200 sensor for color feature extraction. The two features then be processed by Arduino Uno to carry out the classification process into two classes, namely the Normal class and the Sinusitis class. The classification process in this study uses the Support Vector Machine method. The results of the accuracy of the SVM classification get 85% of the 20 data tested. For testing the computational time obtained an average value of 42 milliseconds from as many as 20 test data used.