Sistem Pakar Diagnosis Penyakit Ginjal Kronis Berbasis Web Menggunakan Metode Forward Chaining (Studi Kasus : RSUD Prof. Margono Soekarjo)
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Telkom Purwokerto
Author
Titan, Dwi Fitriani
Subject
T Technology (General)
Datestamp
2021-12-08 04:14:32
Abstract :
Kidney is one of the vital organs in the human body. The year 2018 showed that the prevalence of chronic kidney failure based on a doctor's diagnosis in the population aged over 15 years in Indonesia reached 0.38% or around 739,208 people. The shortage of kidney specialists in Indonesia is one of the challenges in handling because it requires a specialist to diagnose it. Based on this, it is necessary to have an application that can diagnose Chronic Kidney Disease in the form of an expert system as an alternative information and consultation media that is more practical. The expert system was developed using PHP and MySQL. The dataset in this study is primary data from patients with a history of chronic kidney disease from hospitals. Prof. Dr. Margono Soekarjo and there were 70 cases. In designing this system, it was formed using the method Waterfall as a stage in conducting system analysis and the method Forward Chaining as a path tracing in finding the type of disease. Tests carried out using the method Blackbox to test functionality and Confusion Matrix to test accuracy. The accuracy results obtained are 90% for chronic kidney disease and for the average percentage of chronic kidney disease accuracy per stage is 91%. Keywords: Expert System, Forward Chaining, Chronic Kidney Disease, Blackbox, Waterfall
Kidney is one of the vital organs in the human body. The year 2018 showed that the prevalence of chronic kidney failure based on a doctor's diagnosis in the population aged over 15 years in Indonesia reached 0.38% or around 739,208 people. The shortage of kidney specialists in Indonesia is one of the challenges in handling because it requires a specialist to diagnose it. Based on this, it is necessary to have an application that can diagnose Chronic Kidney Disease in the form of an expert system as an alternative information and consultation media that is more practical. The expert system was developed using PHP and MySQL. The dataset in this study is primary data from patients with a history of chronic kidney disease from hospitals. Prof. Dr. Margono Soekarjo and there were 70 cases. In designing this system, it was formed using the method Waterfall as a stage in conducting system analysis and the method Forward Chaining as a path tracing in finding the type of disease. Tests carried out using the method Blackbox to test functionality and Confusion Matrix to test accuracy. The accuracy results obtained are 90% for chronic kidney disease and for the average percentage of chronic kidney disease accuracy per stage is 91%. Keywords: Expert System, Forward Chaining, Chronic Kidney Disease, Blackbox, Waterfall
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
