Image Recognition of Malaria-infected Red Blood Cells among Other Normal and Cancer-Mutated Cells Using CNN

Malaria is a contagious infectious disease that still threatening human life. morbidity when viewed by province shows Eastern Indonesia the area with highest Annual Parasite Incidence (API), namely Papua, West NTT, and Maluku. This concern for continued efforts to control eliminate malaria in these high malaria-endemic areas. There are many strategies help prevent, include possibility of innovation diagnostic process. Therefore, answer how provide technology accelerate elimination malaria, this study aims identify image red blood cells which infected among other normal leukemia cancer-mutated (non-malaria) making improvements through proposed new model used. meant do deep learning using Convolutional Neural Network (CNN). The results obtained show success influenced pre-processing stage, dropout regularization function, rate, momentum value accuracy 0.9660, 0.9693 precision, 0.9626 recall, an F1 score 0.9659.