Simulasi Deteksi Tonsilitis Mengunakan Pengolahan Citra Digital Berdasarkan Warna dan Luasan pada Tonsil

  • Sang Made Lanang Prasetya Universitas Telkom
  • Achmad Rizal Universitas Telkom
  • I Nyoman Apraz Ramatryana Universitas Telkom
Keywords: deteksi, tonsilitis, tonsil, histogram, ROI, k-NN

Abstract

Tonsillitis or known as tonsils is a medical condition characterized by inflammation of the tonsils, causing sore throat, difficulty swallowing, fever, and in certain cases can lead to heart attack or pneumonia. Doctors diagnose tonsillitis in a visual way, see tonsil inflammation and assess subjectively. This study designed a tool to calculate the area of inflamed areas that can be used to help doctors diagnose tonsillitis. Tonsils image processed on the red layer to quantify the extent of tonsils. Furthermore, the red area was calculated as area ofinflammation. In next stage, find the feature extraction using histogram analysis to find the distribution of image intensity levels. The results were classified using k-Nearest Neighbor (k-NN). From 64 datas which consists of 32 normal and 32 tonsillitis, a system can reach 90,625% accuracy rate. This value is achieved at the cityblock distance measurement and k = 1.

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Published
2015-06-04
How to Cite
Sang Made Lanang Prasetya, Achmad Rizal, & I Nyoman Apraz Ramatryana. (2015). Simulasi Deteksi Tonsilitis Mengunakan Pengolahan Citra Digital Berdasarkan Warna dan Luasan pada Tonsil. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 4(1), 45-49. Retrieved from https://journal.ugm.ac.id/v3/JNTETI/article/view/3033
Section
Articles