Abstract

Diabetes Mellitus is one of the non-communicable diseases with the highest proportion in Indonesia and is the sixth highest cause of death in this country. Especially in Asahan District, the number of people with diabetes who died is increasing over time, so there needs to be effective treatment so that diabetes is no longer feared by the public because it is easy to treat. Many patients who experience diabetes are getting worse because they cannot detect the early symptoms of diabetes, which is still considered trivial. There is no information about diabetes and its symptoms, making it difficult to diagnose the disease. In the diagnosis of DM disease is limited to conventional diagnoses with doctors. it is necessary to build a system on a computer application to help diagnose DM. To determine the level of DM disease, an expert diagnostic system was made with the method used in this case is the Bayes method. This method is an approximation to an uncertainty that is measured by probability. Bayes' approach at the time of classification is to find the highest probability by inputting the required attributes and the probability of the disease and related symptoms. The results of the implementation of the system are the selection of symptoms according to the case of experiencing type 1 diabetes because it has a weight = 2 higher than the weight results of other diseases, the system provides the results of the process the system will provide information on what type of DM he is experiencing in order to get a solution with treatment

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call