Yessi Jusman, Ega Samudra, Slamet Riyadi, Siti Nurul Aqmariah Mohd Kanafiah, Amir Faisal, Rosline Hassan, Zeehaida Mohamed
Leukemia or often called blood cancer is one type of cancer caused by excessive white blood cells. Excessive white blood cells will cause disruption of normal function of other blood cells. To find out leukemia, we can do a physical examination in the form of a blood sample or can also use a spinal cord biopsy. In general, doctors take blood samples to see and look for abnormalities of the white blood cell count. To reduce human error in diagnosing leukemia, the study created two systems that can classify leukemia using the Hu moment invariant (HMI) and Support Vector Machine (SVM) methods and the Grey Level Co-occurance Matrix (GLCM) and SVM methods. Classification systems are used to classify acute and normal leukemia image classes using 10-fold cross validation in the sharing of its image data. The best classification results are the GLCM-SVM system with an accuracy value of 99% and the HMI-SVM system produces an accuracy value of 90%. © 2021 IEEE.
Universitas Muhammadiyah Yogyakarta, Faculty of Engineering, Department of Electrical Engineering, Yogyakarta, Indonesia; Universitas Muhammadiyah Yogykarta, Faculty of Engineering, Department of Informatic Tecnology, Yogyakarta, Indonesia; School of Mechatronics Engineering, Universiti Malaysia, Perlis, Malaysia; Institut Teknologi Sumatera, Department Biomedical Engineering, Lampung, Indonesia; Universiti Sains Malaysia, Department of Haematology, Kelantan, Malaysia; Universiti Sains Malaysia, Department of Microbiology and Parasitology, Kelantan, Malaysia