DESIGNING AN EXPERT SYSTEM APPLICATION FOR DIABETES MELLITUS USING THE RANDOM FOREST ALGORITHM

Abstract

Diabetes Mellitus is a disease that infects many people both domestically and abroad. Based on data from the International Diabetes Federation (IDF), in 2021 Indonesia will be ranked number 5 in the number of people suffering from Diabetes Mellitus, namely 19.47 people. Diabetes Mellitus is a disorder of insulin function in the body which usually has general symptoms, namely an increase in blood sugar in humans. In general, Diabetes Mellitus is categorized into two types, namely Diabetes Mellitus type 1 and Diabetes Mellitus type 2. However, many people, especially in Indonesia, have a low level of awareness and awareness of this disease. This is caused by a lack of knowledge about this disease and its risks as well as limited time or costs in consulting a doctor. Therefore, it is necessary to implement artificial intelligence which is applied to the expert system application for Diabetes Mellitus. The design of this expert system application is intended to obtain results in the form of diagnosis, prediction and consultation. This research applies the Random Forest algorithm as a classification algorithm. In its application, this expert system application uses a combination of datasets from the Gotong Royong Surabaya Hospital and public references with a total of 70 rows of data. This algorithm model training uses a ratio of training data to training data, namely 80:20 with an accuracy obtained of 100% and from the confusion matrix evaluation the results obtained were precision of 1.00, recall of 1.00, and f1 score of 1.00. From the results of the accuracy of model training and algorithm evaluation using a confusion matrix, it can be said that the implementation of the Diabetes Mellitus expert system using the Random Forest algorithm is suitable and accurate.