Open AccessDetecting Hand, Foot and Mouth Disease in Earlier Stage Using C4.5 Algorithm as Expert System Based on Android
Author(s) -
Farisa Hafida Syahrial,
Budhi Irawan,
Anggunmeka Luhur Prasasti
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1201/1/012059
Subject(s) - rash , hand foot and mouth disease , disease , decision tree , computer science , enterovirus 71 , decision tree learning , hand foot mouth disease , android (operating system) , medicine , foot and mouth disease , artificial intelligence , machine learning , algorithm , enterovirus , virus , surgery , virology , operating system
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.