Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal Kubik KUBIK: Jurnal Publikasi Ilmiah Matematika
Noormann Atoillah
Universitas Islam Negeri Sunan Ampel Surabaya
Computer Science & IT Economics, Econometrics & Finance Education Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Deteksi Covid-19 Menggunakan Citra X-Ray Metode Gray Level Co-Occurrence Matrix (GLCM) dan Adaptive Neuro Fuzzy Inference System (ANFIS) Fitri Mellynia Astiti; Noormann Atoillah; Rahmat Rizki Sinulingga; Achmad Room Fitrianto
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The first detected COVID-19 was in China, this virus has spread worldwide rapidly. COVID-19 is caused by the SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Corona Virus-2) or an acute infection that attacks the respiratory system. COVID-19 examination can be carried out by X-rays. The X-ray images will be identified using a CAD system or Computer-Aided Diagnosis. CAD has three processes consisting of preprocessing, feature extraction, and classification. This study compares 200 X-ray image data of COVID-19 data and 200 X-ray image data of non-COVID-19 data. Both groups of data were divided using the K-fold Cross Validation method where the K value used is 10 so that the distribution of training data is 90% and testing is 10%. The epoch used is 5 with 4 parameters (contrast, correlation, energy, and homogeneity). In the feature extraction process, GLCM is used by comparing every angle in the feature extraction, while Adaptive Neuro Fuzzy Inference System (ANFIS) is used for classification. The best results were obtained from GLCM at an angle of 0° with an accuracy value of 0.90, a sensitivity of 0.85 and a specificity of 0.95. This shows that the use of GLCM and ANFIS for COVID-19 detection performs well.
Deteksi Covid-19 Menggunakan Citra X-Ray Metode Gray Level Co-Occurrence Matrix (GLCM) dan Adaptive Neuro Fuzzy Inference System (ANFIS) Fitri Mellynia Astiti; Noormann Atoillah; Rahmat Rizki Sinulingga; Achmad Room Fitrianto
KUBIK Vol 7, No 2 (2022): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The first detected COVID-19 was in China, this virus has spread worldwide rapidly. COVID-19 is caused by the SARS-CoV-2 virus (Severe Acute Respiratory Syndrome Corona Virus-2) or an acute infection that attacks the respiratory system. COVID-19 examination can be carried out by X-rays. The X-ray images will be identified using a CAD system or Computer-Aided Diagnosis. CAD has three processes consisting of preprocessing, feature extraction, and classification. This study compares 200 X-ray image data of COVID-19 data and 200 X-ray image data of non-COVID-19 data. Both groups of data were divided using the K-fold Cross Validation method where the K value used is 10 so that the distribution of training data is 90% and testing is 10%. The epoch used is 5 with 4 parameters (contrast, correlation, energy, and homogeneity). In the feature extraction process, GLCM is used by comparing every angle in the feature extraction, while Adaptive Neuro Fuzzy Inference System (ANFIS) is used for classification. The best results were obtained from GLCM at an angle of 0° with an accuracy value of 0.90, a sensitivity of 0.85 and a specificity of 0.95. This shows that the use of GLCM and ANFIS for COVID-19 detection performs well.
Co-Authors Achmad Room Fitrianto Fitri Mellynia Astiti Rahmat Rizki Sinulingga