Application-Based on Fuzzy Tsukamoto And Profile Matching for Combination Drugs Recommendations in Patients Hypertension with Complications

Abstract

Hypertension is still the number one killer disease in Indonesia, and hypertension sufferers have
increased by 8.3% per year from 2013-2018. In 2018 the prevalence of hypertension in Indonesia reached
34.1% and affected about 20% of the world's population. Handling of hypertension sufferers can be done in
two ways, namely modifying lifestyle and using drugs. Antihypertensive drugs that are given pay attention to
age, history of the disease, smoking habits, obesity, and consider diseases such as diabetes, kidney, heart
failure, and ischemic heart. Improper use of antihypertensive drugs often causes fever, diarrhea, diabetes,
kidney failure, stress, breathing through the mouth, neurological disorders, radiation to the neck and head
area, and localized disorders of the salivary glands. Doctors or medical personnel in providing
antihypertensive drugs require good pharmacological knowledge. In general, not all hospitals have someone
who is an expert in pharmacology. Therefore this study aims to develop a model based on Fuzzy Tsukamoto
and Profile Matching for a recommendation of drug combinations, the suitability of dosage, and frequency in
hypertensive patients. The results of the model evaluation show an accuracy of 97.5%