IMPLEMENTATION OF C4.5 ALGORITHM FOR EARLY DETECTION OF DIABETES MELLITUS IN HUMANS
Abstract
Diabetes is classified as one of the fastest-growing life-threatening chronic diseases that has affected 422 million people worldwide according to a World Health Organization (WHO) report, in 2018. Therefore, it is very important to do early detection of DM because if the disease is left too long without treatment, it can result in dangerous complications such as kidney failure, damage to other organ functions to heart attacks. In this research, an information system will be built by applying the C4.5 data mining algorithm for early detection of Diabetes Mellitus in humans. The dataset in this study was taken from the Kaggle Diabetes Dataset. The results showed that the information system built can help the medical world in conducting early detection of Diabetes Mellitus in humans through prediction features that implement the C4.5 algorithm. In addition, the results of testing the C4.5 algorithm show that the algorithm is classified as accurate in predicting early detection of Diabetes Mellitus if it follows the rule of the decision tree formed.
