In recent years, the diabetes mellitus in Indonesia has
become a health problem in the community because its population has increased
2-3 times faster than other countries. Diabetes prevalence in Indonesia ranks
4th highest in the world after China, India and the United States. People can
prevent complications and premature death if they detect early symptoms of
diabetes. However, people do not know that they are at risk of diabetes, not
had knowledge about the symptoms of diabetes, complexity of the process
diagnosis and the high cost of examinations. Therefore, we need an application
that can provide the results of the type of diabetes and its management
solutions as practiced by experts. The aim of this research is to develop an
expert system for detection types of diabetes such as: type one diabetes, type
two diabetes, neuropathy diabetes, diabetes retinopathy, and diabetes
nephropathy. The object of this research is diabetes carried out in March to
April 2019 in the Klinik Pratama Desa Putera. This study uses primary data from
patients who had a history of diabetes at Klinik Pratama Desa Putra and
secondary data in the form of literature, research journals, and data documents
needed to compile this study. In addition, we generated a knowledge base using
forward chaining. The test results show that the expert system meets the
functional requirements and the system performance reaches an accuracy of 100%.
This expert system helps people in Indonesia to detect diabetes early so that
it can prevent complications.
Peer Review Jurnal JRI Vol. 2, No. 2 Maret 2020
Artikel JRI Vol. 2, No. 2 March 2020
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