Intelligent Prediction and Detection of Diabetes Mellitus Using Machine Learning

Abstract

One of the diseases with a fairly high number of sufferers today is Diabetes Mellitus. The increase in the number of people with diabetes is caused by delays in diagnosis and also difficulties in monitoring the blood sugar level. Therefore, a solution is needed to overcome this problem, namely a blood sugar level monitoring system to predict and detect. The blood sugar level monitoring system is an intelligent system that can monitor blood sugar levels in Diabetes Mellitus patients. This system aims to make it easier for patients to check blood sugar levels regularly, to minimize the occurrence of increased blood sugar levels that aggravate the disease. Moreover, machine learning algorithms are a viable method used in recent studies for analyzing, predicting, and classifying health data while improving the health conditions of telemonitoring and telediagnosis. The main purpose of this article is to employ machine learning algorithms for blood sugar level classification in real time. The results of this study indicate that the system can be used to monitor blood sugar levels. The results of the implementation of the system that can be used by users include monitoring the results of measuring blood sugar levels.
 Keywords: Monitoring Machine Learning, Prediction, Diabetes Mellitus, Data Mining