scholarly journals Sistem Pakar Diagnosa Awal Penyakit Mata dengan Metode Bayesian Network

2020 ◽  
Vol 4 (2) ◽  
pp. 139-148
Author(s):  
Novanita Laylatul Husna ◽  
Fitri Bimantoro
Keyword(s):  
Expert System ◽  
Bayesian Network ◽  
Rapid Assessment ◽  
Eye Disease ◽  
Accuracy Rate ◽  
The Public ◽  
System Diagnosis ◽  
Network Method ◽  
Community Facilities ◽  
Clear Information

Almost every human activity needs an eye to support these activities, therefore it will have a bad effect if the eyes experience interference. Disorders that can be experienced in the eye can occur from minor disorders to disorders that cause loss of vision and even death. Based on the results of the Rapid Assessment Assessment of Avoidable Blindness (RAAB), the blindness rate in districts/cities in NTB was 4%. This is not only due to medical-related problems but also due to social problems related to knowledge from the community, facilities, and resources. To make it easier for the public to make an initial diagnosis of eye disease, one thing that can be done is to use an expert system. Various methods can be implemented for expert systems, one of which is the Bayesian Network method. Based on the results of accuracy testing that has been done, this application provides an accuracy rate of 84.99%. Whereas, if the system diagnosis results are a subset of expert diagnostic results, the accuracy rate is 89.99% and based on the results of the use made by the general public, this application has been running well and has provided clear information related to the diagnosis of eye disease.

scholarly journals Sistem Pakar dalam Mendiagnosis Penyakit Mata dengan Menggunakan Metode Forward Chaining

2021 ◽  
pp. 128-133
Author(s):  
Budi Permana Putra ◽  
Yuhandri Yunus ◽  
Sumijan
Keyword(s):  
Expert System ◽  
Human Life ◽  
The Body ◽  
Eye Disease ◽  
Early Prevention ◽  
The Public ◽  
Forward Chaining ◽  
Eye Health ◽  
Eye Problems ◽  
Visual Disturbances

The eye is one of the organs in the body that has an important role in human life, because the eye is one of the organs that has a function as vision in carrying out every activity. Eye health really needs to be maintained by diligently consulting or having your eyes checked by a doctor so that vision remains clear and there are no eye problems when looking at objects around us. However, eye health is often neglected, so that many various diseases can attack the eye. If not handled properly, diseases that attack the eye can cause visual disturbances and lead to blindness. Therefore, the eye must be kept healthy and kept clean because it is a very important organ of the human body. The purpose of building this expert system is to assist the public in diagnosing eye diseases from the symptoms that are being felt. This expert system will be a way out of eye problems that are suffered by the community, In this way people no longer have trouble going to the doctor. All data and facts to be processed are obtained from an expert, the method used in diagnosing this eye disease is the forward chaining method to apply the rules of the 28 symptoms and 8 diseases described by the expert. The results of the diagnosis using the Forward Chaining method is a very good level of accuracy in determining the type of eye disease that is suffered by the community and can provide early prevention for users who use this expert system.

scholarly journals Rancang Bangun Aplikasi Sistem Pakar Berbasis Android untuk Identifikasi Penyakit pada Gigi dengan Menggunakan Metode Forward Chaining

2021 ◽  
Vol 5 (4) ◽  
pp. 459
Author(s):  
Johan Limantono ◽  
Rinabi Tanamal
Keyword(s):  
Expert System ◽  
Dental Health ◽  
The Body ◽  
Test Results ◽  
Digestive Process ◽  
The Public ◽  
Forward Chaining ◽  
System Diagnosis ◽  
Dental Diseases ◽  
Food Conditions

Teeth are an important part of the body in the digestive process. As a start of the digestive process, teeth receive various kinds of food conditions such as sweet, cold, hard foods, and so on. These food conditions affect dental health so that when teeth are not treated they become vulnerable to disease. Society in general does not pay attention to pain in the teeth. Though the pain in the teeth can be caused by diseases such as dental caries, tartar, and others. The solution of this research is manifested in the form of an expert system to diagnose dental diseases using the Android-based Forward Chaining method. The expert system application used by researchers is McGoo. The purpose of this expert system is to help the public get information and carry out a diagnosis of dental disease independently. Users only need to answer the questions displayed by the system to get the results of the diagnosis in the form of the type of illness and treatment solutions that can be done. The results of the system diagnosis have been tested and validated by experts namely dentists who are the source of information and data. Based on the accuracy of the system diagnostic test results are by the results of the expert diagnosis.

scholarly journals Expert System Diagnosis Dental Disease Using Certainty Factor Method

2017 ◽  
Vol 4 (1) ◽  
pp. 43-50 ◽  
Author(s):  
Whisnu Ulinnuha Setiabudi ◽  
Endang Sugiharti ◽  
Florentina Yuni Arini
Keyword(s):  
Expert System ◽  
Measurement Accuracy ◽  
Technological Development ◽  
Disease Diagnosis ◽  
Dental Disease ◽  
Certainty Factor ◽  
Accuracy Rate ◽  
Human Needs ◽  
Factor Method ◽  
System Diagnosis

Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate.

scholarly journals Sistem Pakar Diagnosa Penyakit Mata Menggunakan Metode Certainty Factor Berbasis Android

2018 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Yogi Permana ◽  
I Gede Pasek Suta Wijaya ◽  
Fitri Bimantoro
Keyword(s):  
Expert System ◽  
System Application ◽  
Early Treatment ◽  
Eye Diseases ◽  
Health Centers ◽  
Doctor Who ◽  
Certainty Factor ◽  
Accuracy Rate ◽  
System Diagnosis ◽  
Android Applications

This entitled of research "Expert System Diagnosis Eye Diseases Using MethodCertainty Factor Based Android" is proposed due to the increased spread eye diseases thatis leads to blindness in Indonesia it is happened because of the limited facilities of eyehealth services in health centers and hospitals, as well as lack of eye doctor who canexamine the eye, making eye left untreated and can cause serious damage to the eye.Therefore, many people are already suffering from the early symptoms of blindnessletting untreated without properly treatment. The purpose of this study is to develop anexpert system that is capable of providing information about eye diseases along withsuggested solutions of the disease suffered by imitating the analysis of an eye doctor.The system is built using certainty factor method which is an algorithm that isimprove the uncertainty idea of an expert. This method is used to describe the level ofconfidence of experts on issues being addressed. This system is built by Ionic frameworkfor Android applications with PHP, HTML5 and AngularJS.The system is able to provide information about eye diseases through the processof diagnosis, that can be used for early treatment of eye diseases. The whole function ofthis expert system application already worked properly without any mistakes. Anddiagnostics accuracy rate of the system is 75% in the diagnosis process of 15 diseases and52 symptoms.

scholarly journals Sistem Pakar dengan Menggunakan Metode Naive Bayes dalam Mengidentifikasi Penyakit Karies pada Gigi Manusia

2021 ◽  
pp. 233-238
Author(s):  
Tio Ramadan Sapto Hari ◽  
S Sumijan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Tooth Decay ◽  
Test Results ◽  
Accuracy Rate ◽  
Bayes Method ◽  
Human Teeth ◽  
The Public

Caries disease in human teeth is a disease that permanently destroys the inner walls of teeth and forms small holes in the teeth. The Indonesian people lack the knowledge to find information and identify tooth decay, which makes many people unaware of the consequences and dangers of this disease. Tooth decay disease is usually caused by three factors. The first factor is teeth and saliva, which are the hosts of microorganisms in the oral cavity. Bacteria and food are the second and third factors. The purpose of this research is to help the public find information about tooth decay, thus forming a branch of artificial intelligence, the expert system. Artificial intelligence is a science that allows you to build computer systems that display intelligence in different ways. An expert system is a computer program or information system that uses some knowledge of an expert. The methods used in this study are the Naive Bayes method and the model's view controller, which are implemented as a database in the PHP Codeigniter framework and MySQL. The data processed in this study is knowledge about the symptoms of dental caries obtained from experts. The test results of this method provide patients with the knowledge necessary to prevent tooth decay, with an accuracy rate of 83.61%. This expert system helps the public to recognize and obtain information about tooth decay. The Expert System can also be used to take the first step in preventing tooth decay.

A Resamping Approach for Customer Gender Prediction Based on E-Commerce Data

2017 ◽  
Vol 3 (1) ◽  
pp. 76 ◽  
Author(s):  
Duong Tran Duc ◽  
Pham Bao Son ◽  
Tan Hanh ◽  
Le Truong Thien
Keyword(s):  
Data Mining ◽  
Bayesian Network ◽  
Web Applications ◽  
Service Providers ◽  
Main Idea ◽  
Classification Methods ◽  
Cost Sensitive Learning ◽  
Network Method ◽  
Demographic Attributes ◽  
Privacy Issues

Demographic attributes of customers such as gender, age, etc. provide the important information for e-commerce service providers in marketing, personalization of web applications. However, the online customers often do not provide this kind of information due to the privacy issues and other reasons. In this paper, we proposed a method for predicting the gender of customers based on their catalog viewing data on e-commerce systems, such as the date and time of access, the products viewed, etc. The main idea is that we extract the features from catalog viewing information and employ the classification methods to predict the gender of the viewers. The experiments were conducted on the datasets provided by the PAKDD’15 Data Mining Competition and obtained the promising results with a simple feature design, especially with the Bayesian Network method along with other supporting techniques such as resampling, cost-sensitive learning, boosting etc.

Rancang Bangun Sistem Pakar Prediksi Stres Belajar Dengan Neural Network Algoritma Backpropagation

2016 ◽  
Vol 7 (2) ◽  
pp. 105-112
Author(s):  
Adhi Kusnadi ◽  
Idul Putra
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Stress Level ◽  
Network Structure ◽  
Human Being ◽  
Accuracy Rate ◽  
Backpropagation Algorithm ◽  
Stress Prediction ◽  
Index Terms ◽  
Hidden Nodes

Stress will definitely be experienced by every human being and the level of stress experienced by each individual is different. Stress experienced by students certainly will disturb their study if it is not handled quickly and appropriately. Therefore we have created an expert system using a neural network backpropagation algorithm to help counselors to predict the stress level of students. The network structure of the experiment consists of 26 input nodes, 5 hidden nodes, and 2 the output nodes, learning rate of 0.1, momentum of 0.1, and epoch of 5000, with a 100% accuracy rate. Index Terms - Stress on study, expert system, neural network, Stress Prediction

SISTEM PAKAR MENENTUKAN PENYAKIT GINJAL DENGAN METODE FORWARD CHAINING

2020 ◽  
Vol 11 (1) ◽  
pp. 27-32
Author(s):  
Wahyu Alfandry Pulungan
Keyword(s):  
Expert System ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Metabolic System ◽  
Consultation Process ◽  
The Public ◽  
System Disease ◽  
Visual Basic 6.0 ◽  
High Calorie ◽  
Selection Of

Selection of issues regarding the kind of kidney disease as a sample of this study, is the fact that diseases Kidney is an important organ in our body's metabolic system, because the density of activity, we often forget to take care of. Irregular diet, inadequate intake of fiber and mineral water, as well as the consumption of food or drink high calorie instant, unwittingly aggravate the kidneys. Starting from the filtration, reabsorption, to augmentation of nutrients that under to the kidneys via the blood. The purpose of this research is to build an expert system Kidney disease using Visual Basic 6.0 programming language that is capable of providing services to the public and delivery of information related to kidney disease. In this research, data collection is done by using the method of observation, interviews, and literature. From the results of this study indicate that the presence of kidney disease diagnosis expert system in humans can provide significant benefits, among others, the processing of data and consultation process carried out quickly and produce a fairly accurate report, thus making the job more effectively and efficiently. Keywords: Expert System, Disease, Kidney, Human.

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