Image Classification of Abnormal Red Blood Cells Using Decision Tree Algorithm

The study aims to increase the number of abnormal red blood cells that can be detected using image processing. This study used Decision-Tree Algorithm as a machine learning algorithm in classifying. As a result, the system detected and classified a total of ten abnormal red blood cells. Images used in the system came from hospitals’ past patients. In addition, a camera is used to capture the slides. The image was then inserted into the program. The system processed and classified the image. In effect, the results show the name of the abnormal red blood cells detected in the image within the system including the soft copy of the list.