Sistem Pendukung Keputusan Menggunakan Fuzzy Logic Tahani Untuk Penentuan Golongan Obat Sesuai Dengan Penyakit Diabetes - Charolina Debora Mait; Josua Armando Watuseke; Prince David Gibrael Saerang; Salaki Reynaldo Joshua (UNIVED Press, 2022)
Abstract: Consuming foods and drinks that contain a lot of Glucose, allows the risk of developing Diabetes. Diabetes is a disorder of the metabolic system of carbohydrates, proteins, and fats in the body due to disturbances that occur in insulin secretion that cause a decrease in insulin performance. Please be aware that Diabetes can lead to death, blindness, heart disease and kidney failure. According to data from the International Diabetes Federation in 2019, Indonesia is ranked 7th, where 10.7% of the total population suffers from Diabetes. For this reason, we are interested in making fuzzy logic on determining drug classes in diabetes based on the patient's blood glucose levels. The purpose of this study is to prove that fuzzy logic can be a solution for classifying drugs in diabetic patients. We'll create a fuzzy Logic that uses The Hard Way graphic model on each variable membership function. For the fuzzy manufacturing process toolbox we used a Jupyter Notebook on anaconda Navigator.The limitation of the study is the use of doses on drugs. This research can contribute to the field of health. Keywords: Fuzzy Logic, Artificial Intelligence, Diabetes, Jupyter Notebook, Tahani Method.