Arika Juwita Z
Universitas Putra Indonesia YPTK Padang

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Sistem Pakar Menggunakan Metode Forward Chaining pada Tingkat Kesembuhan Terapi Farmakologi dan Gaya Hidup Sehat Terhadap Pasien Hipertensi Arika Juwita Z; Sarjon Defit; Yuhandri Yunus
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i1.82

Abstract

Hypertension is blood pressure above normal caused by strong blood flow to the walls of the arteries, resulting in certain complications that are at risk of triggering heart disease, stroke, kidney failure and even death. Many people do not know about the symptoms and types of hypertension, so a system is built to make it easier for the medical team and system users to find out the types of hypertension along with the cure rate with pharmacological and lifestyle therapies. The purpose of this study was to determine the cure rate of pharmacological therapy and a healthy lifestyle for hypertensive patients based on data collected from experts. The data that were processed were 25 symptoms, 2 therapy data, and 8 types of hypertension based on blood pressure classification. The symptoms and types of disease are entered into the expert system using the Forward Chaining method and rules. To see the accuracy of the cure rate for pharmacological therapy and a healthy lifestyle for hypertensive patients, a Forward Chaining method is needed, namely: Prepare data input, define decision tables, define rules, perform processes that create decision trees. The results of the study with 25 symptom data obtained as many as 8 decision rules, namely which type of hypertension the patient has and which cure should be done. Based on the analysis carried out, it can be seen that the cure rate of pharmacological therapy and a healthy lifestyle can be used as a reference for making decisions to analyze the healing of hypertensive patients with pharmacological therapy and a healthy lifestyle. This expert system calculation shows the percentage of success from the expert.