Expert System Diagnosis of Kidney Disease Using Forward Chaining

Abstract

Kidney disease is a disease that is often experienced by people aged over 50 years. Several factors that cause kidney disease include hypertension, diabetes, obesity, smoking and family history of kidney disease sufferers. As many as 42,000 people per year die from kidney disease. Sufferers in Indonesia, which is estimated by the Ministry of Health, based on the 2013-2018 Basic Health Research (Riset Kesehatan Dasar (RIKESDA)) the number of patients experiencing kidney disease symptoms continues to grow to reach 739,208 people in 2013 while chronic kidney sufferers. It was recorded that in 2020 BPJS Kesehatan spent a large enough budget for kidney failure patients as many as 1,763,260 patients. The high number of patients with kidney disease was due to a lack of physical activity and consumption of healthy foods and fruits and vegetables. Therefore, it is necessary to detect as early as possible to prevent the onset of kidney disease. Technology is one of the disseminations of good information in handling kidney disease. This study aims to build an expert system for diagnosing kidney disease. The results of the research on an expert system for diagnosing kidney disease based on a website that can be accessed by the public by providing information on the detection of kidney disease symptoms with 27 symptoms. The process of tracking symptoms using forward chaining. Conclusion tests carried out using black box and usability testing have been running well, as seen from the input and output functionality on the system used by the user. In addition, the expert system helps in providing information to the public to detect the symptoms of kidney disease as early as possible.