JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Vol 5 No 2 (2021): December 2021

Klasifikasi K-NN dalam Identifikasi Penyakit COVID-19 Menggunakan Ekstraksi Fitur GLCM

Nisa Nafisah (Unknown)
Riza Ibnu Adam (Unknown)
Carudin Carudin (Unknown)



Article Info

Publish Date
22 Oct 2021

Abstract

Covid-19 is a disease that is endemic in various parts of the world including Indonesia, this disease infects the respiratory tract caused by a new type of corona virus. To find out the presence of this virus in the body, medical examinations such as blood tests, radiological examinations can be carried out X-rays (x-rays) and swabs. Therefore, in this study, identification covid-19 disease based on the rongen image from which the image was extracted using the GLCM feature extraction method, namely contrast, correlation, energy, and homogeneity, after obtaining the value from the extraction and then classified using data mining classification method, namely k-nearest neighbor by doing 3 modeling the input value of k. The results obtained from the classification obtained an accuracy of 80% in model 3 with a value of k = 5 and in models 1 and 2 obtained an accuracy of 90% with a value of k = 1 and k = 3.

Copyrights © 2021






Journal Info

Abbrev

JAIC

Publisher

Subject

Computer Science & IT

Description

Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan ...