Detecting Hand, Foot and Mouth Disease in Earlier Stage Using C4.5 Algorithm as Expert System Based on Android
Farisa Hafida Syahrial, Budhi Irawan, Anggunmeka Luhur Prasasti · Journal of Physics Conference Series · 2019
Abstract Hand, Foot and Mouth Disease (HFMD) is an infectious diseases caused by enterovirus virus 71 (EV 71). The symptoms of HFMD is similar to several other disease that caused by a virus, especially disease that have a fever and rash symptoms which people usually underestimate diseases that have early symptoms like that. Therefore, in this system we classify the HFMD with the intention of detecting the disease from an earlier stage. And we use Android based application since at this present time, smartphone is the closest device that is always used by many people. The classification used in this paper is Decision Tree C4.5 Algorithm. Dataset used in this research is as many as 256 which divided into training data and testing data, that formed based on symptoms that had previously been validated by the doctor. The result shows that data partitions of 90%:10%, 80%:20% and 70%:30% has accuracy, precision and recall value are 100%. Thus, data partition 70%:30% has the best result because this partition has less training data but can still classify diseases effectively.