Deteksi Covid-19 Menggunakan Citra X-Ray Metode Gray Level Co-Occurrence Matrix (GLCM) dan Adaptive Neuro Fuzzy Inference System (ANFIS)

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

"Der Islam" in Deutschland. Transformationsprozesse muslimischer Religiosität in der Diaspora

Der Autor stellt vor dem Hintergrund einer religionswissenschaftlichen Migrationsforschung die historisch gewachsene Bedeutung des Islams in Deutschland dar. Dabei kommen Möglichkeiten und Grenzen von Transkulturalität in den Blick. (DIPF/Orig.)The author presents the historically growing importance of the Islam in Germany with the background of a migration research on religious science. Thereby, chances and limits of transculturality come into focus. (DIPF/Orig.