IMPLEMENTASI KESESUAIAN OBAT PADA PENYAKIT MENGGUNAKAN ALGORITMA APRIORI - Yennimar Yennimar; Evan Chandra Sibarani; Irwansyah Irwansyah; Muhammad Iqbal Tri Rahmadi; Reza Syahputra (Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan)
Health is important for every living thing, especially humans. there are several things that are important in maintaining health, including eating high-energy foods and foods that have vitamins. However, sometimes the disease can not be guessed. Disease can attack our bodies, especially diabetes.Diabetes is a disease that lasts a long time or chronic, and is characterized by high blood sugar (glucose) levels or above normal values. If diabetes is not well controlled, it can cause various complications that can endanger the lives of patients. Because this disease is dangerous, so not just drugs can cure this disease. Appropriate drugs are needed to treat this disease, drugs that are suitable for this disease can be seen based on which drugs are often purchased by patients. Therefore we need a data collection algorithm / basket that has high accuracy. Apriori is one of the data collection algorithms using a basket that has a high accuracy that reaches 80%. The data we use in this study reached 1000 drug data but only 27 types of diabetes drugs that we use. and consists of 365 contractions.The purpose of this study is to recommend which drugs are most suitable for patients by finding which drugs are often purchased at Royal Prima Indonesia Hospital. The application that researchers use in this study is the WEKA application.