LAUSR

Malaria is one of the global diseases, which mostly found in eastern Indonesia. It is caused by Plasmodium parasite infection, with four type of common species that are Plasmodium ovale (PO), Plasmodium Malaria (PM), Plasmodium falciparum (PF) and Plasmodium vivax (PV). Malaria can be detected by taking a microscopic analysis from a patient blood sample. Although it is a gold standard of malaria identification according to the WHO, this method has a risk of miss diagnosis due to the human factors. This study proposed a classification method with morphological features of PM and PO in order to help the medical expertise in identifying the malaria parasite from a thin blood smear digital microscopic image. The data used are digital images that have been through the Region of Interest (ROI) determination process. Furthermore, the process followed by improving the morphological and feature extraction of shapes and colors. Based on these obtained features, the parasites are classified by using the multilayer perceptron method. From this study, we found that the classification system has the accuracy of 95%, the sensitivity of 93%, and the specificity of 97%.