Perancangan Sistem Diagnosis Kesehatan Manusia Melalui Screening Digital Berbasis Desktop Application Menggunakan Metode Forward Chaining dan Neural Network

Design of a Human Health Diagnosis System Through Desktop Application-Based Digital Screening Using Forward Chaining and Neural Network Methods

Abstract

One of the problems with hospital services is that queues are important because they affect hospital productivity. Hospital queues can be caused by the large number of patients and the length of time the patient is treated. According to the Regulation of the Minister of Health of the Republic of Indonesia Number 30 of 2022, the standard of patient satisfaction with health services must reach ≥ 90% where one indicator is the length of waiting time. Long waiting times or queues can cause medical services to be less than optimal, especially for patients who have emergency complaints. Therefore, to increase the productivity of hospital services, a human health diagnosis system was designed through digital screening to make it easier for doctors to diagnose patient illnesses. The design of this disease diagnosis system was carried out using methods using forward chaining and neural network methods. This innovation is also equipped with severity level detection and treatment recommendations to patients. This research aims to create a knowledge model that can predict patient disease. The effectiveness test was carried out by taking 15 samples of respondents who had different symptoms. The results of this research were that the accuracy level of patient disease diagnosis testing reached 86.6% with the functional capability of the designed diagnostic application functioning at 100%. With this innovation, diagnosis of symptoms of human disease can be carried out precisely and precisely so that it can help medical personnel in increasing hospital productivity and the level of health in every community in Indonesia.