Identifikasi Acute Lymphoblastic Leukemia pada Citra Mikroskopis Menggunakan Algoritma Naïve Bayes

• Main Authors: Shofiya Syidada, Bagus Hariyanto
• Format: Article
• Language: English
• Published: Lembaga Penelitian dan Pengabdian kepada Masyarakat 2021-03-01
• Series: Rekayasa
• Subjects: acute lymphoblastic leukemia; microscopic image; naïve bayes classifier; thresholding
• Online Access: https://journal.trunojoyo.ac.id/rekayasa/article/view/9110

Leukemia is a type of blood cancer that occurs when the body overproduces abnormal white blood cells. Acute Lymphoblastic Leukemia (ALL) is a type of acute leukemia. ALL occurs when the spinal cord is excessively producing young lymphocytes, known as lymphoblasts. Leukemia is difficult to detect because it has the same symptoms as other diseases. One way to detect leukemia is to use a complete blood count test. Blood count test is done by calculating the population of red blood cells, white blood cells and platelets. The health condition of the body is indicated by the number of each blood cell. The small number of erythrocyte and abnormal cell shape is indicative of leukemia. How to identify leukemia still using a microscope. In this study the researchers made a way of identifying acute lymphoblastic leukemia cells by image processing, include cropping, segmentation, feature extraction and identification. The method used in image identification is Naïve Bayes Classifier (NBC). NBC is a classification method which applies simple probability calculations using Bayes theorem. The white blood cell image tested using this application will be evaluated with accurations. The greatest accuracy results from several test scenarios obtained 80% accuracy.