IDENTIFIKASI PENYAKIT TUBERKULOSIS DENGAN DETEKSI POLA SPUTUM SMEAR MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN

Moch. Adhari Adiguna

Abstract


Information technology in terms of image processing supports a variety of fields, such as medicine, robotics, geology, military, and others. In the field of medicine how to process images in micro-order, for example, the diagnosis of tuberculosis from sputum smear. According to the WHO sputum smear examination is widely used for the diagnosis of tuberculosis (WHO, 2013). Sputum examination is important because it can be the discovery of germs mycobacterium tuberculosis, so that the diagnosis of tuberculosis can be ascertained (Amin and Bahar, 2007). Additionally microscopic examination of sputum more done because of the high sensitivity, in addition to the low cost (Ayush Goyal, Mukesh Roy, Prabhat Gupta, Malay Kishore Dutta, Sarman Singh, Vandana Garg, 2015). This thesis has been designed decision support system application for tuberculosis disease with sputum smear detection pattern using artificial neural network method. Experiments performed in this study using 132 image size of 300 x 400 pixels which is obtained from the results of observations in the laboratory BBKPM (Balai Besar Kesehatan Paru Masyarakat) Bandung, however that image is less good because the image obtained from 3x magnification, so also tested public dataset of the Indira Gandhi Medical College (IGMC) Shimla form of sputum smear 137 images size of 800x600 pixels. The trial results of this application obtained 89.78% sensitivity level within one minute and seven seconds from the input image of sputum smear.

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References


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