scholarly journals Expert System to Diagnose Malaria With Bayes Method

2020 ◽  
Vol 2 (1) ◽  
pp. 88-92
Author(s):  
Mei Melan Rut Sartika Hutapea ◽  
R. Mahdalena Simanjorang
Keyword(s):  
Expert System ◽  
Bayesian Methods ◽  
Tropical Climate ◽  
Anopheles Mosquito ◽  
Public Cloud ◽  
Bayes Method ◽  
Disease Symptoms ◽  
Deadly Disease ◽  
Lack Of Knowledge

Malaria is a deadly disease. The disease is caused by a virus that is transmitted through the bite plasmadium Anopheles mosquito tropics. , Indonesia is an area that has a tropical climate so that malaria prevalent in Indonesia. Many public cloud lack of knowledge about the symptoms of malaria because malaria disease symptoms similar to the usual feverish illness. If the disease is not handled seriously can lead to death. From the above explanation makes the excuse needed one expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. In the expert system there are several methods used to menagani a problem. With the solution given institute Bayes Method in helping to diagnose diseases, the expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. expert system that can help people diagnose malaria by looking at symptoms, and later this expert system can explain and diagnose whether a disease malaria or not. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation. Expert System is generally defined as a system that is able to region contribute to solving or handling problems. Expert System is not intended to replace the expert, but to help and support experts. Bayesian methods can diagnose simple encoding and faster calculation.

scholarly journals Expert System for Diagnosing Diseases Tubercolosis Using Bayes Method In Puskesmas Petumbukan

2020 ◽  
Vol 2 (1) ◽  
pp. 7-14
Author(s):  
Muhammad Ridho Syahwana ◽  
R. Mahdalena Simanjorang
Keyword(s):  
Infectious Disease ◽  
Chronic Disease ◽  
Expert System ◽  
Bayesian Methods ◽  
Bayes Method ◽  
Acid Fast Bacilli ◽  
Microsoft Access ◽  
Long Time ◽  
Tuberculosis Disease

Tuberculosis is an infection caused by acid-fast bacilli (AFB). Tuberculosis is an infectious disease apat affect anyone over the air. Tuberculosis is an infectious disease berbahaya.Tuberculosis a chronic or chronic disease that can strike between the age of 15-35 years. How to diagnose tuberculosis is by way of the expert of experts interviewed then test sputum samples using a lab to determine the positive or negative tuberculosis disease so it takes a long time. Therefore it takes an expert system with Bayesian methods to facilitate the penykit diagnosing tuberculosis. This expert system developed using Microsoft Visual Studio 2010 as well as by using Microsoft Access 2010 database.

scholarly journals SISTEM PAKAR DIAGNOSA PENYAKIT DAN HAMA PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAIVE BAYES

2021 ◽  
Vol 2 (3) ◽  
pp. 390-398
Author(s):  
Bayu Bastiyan Suherman
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Preventive Measures ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Agricultural Commodities ◽  
Bayes Method ◽  
Mathematical Basis ◽  
Lack Of Information ◽  
Corn Plants

Corn is one of the leading agricultural commodities that can be used as a staple plant other than rice. Constraints faced by corn farmers include the lack of information about diseases that attack the corn plants, which causes less productivity. In this study a system was developed that can automatically detect disease that attacks corn plants so that preventive measures can be taken to prevent corn plants from dying. Expert systems are designed to solve certain problems by imitating the work of experts. In addition, this expert system also helps farmers who are experiencing problems regarding diseases and pests and their solutions without relying on an expert. The method used is the Naive Bayes method, Naive Bayes is a method used to predict probabilities and has several characteristics that are istitively in accordance with the way of thinking of an expert and accompanied by a strong mathematical basis. From the tests carried out with diagnoses obtained from the comparison between the results of expert diagnoses and the diagnosis of the system to diagnose diseases and pests in corn plants is 90%.

ANN based Expert System to Predict Disease in Cardiac Patients at Initial Stages

2015 ◽  
Vol 6 (2) ◽  
pp. 1-9
Author(s):  
Umer Rashid
Keyword(s):  
Expert System ◽  
Cardiac Disease ◽  
Preliminary Investigation ◽  
Cardiac Patients ◽  
Cardiac Abnormality ◽  
Human Beings ◽  
Disease Symptoms ◽  
Minimum Error ◽  
Heart Abnormalities ◽  
Artificial Neural Network Ann

Objective of this research is to develop an expert system for the preliminary investigation of cardiac abnormality in human beings. Artificial Neural Network (ANN) is judged best for the prediction of heart abnormalities in cardiac patients at initial stages. Our research is intended to employ an Artificial Intelligence (AI) technique in an automated solution, having minimum error bounds. An ANN based expert system is designed and developed, which identifies presence or absence of cardiac disease in patients by considering best practiced disease symptoms. The proposed expert system may help the clinicians in the preliminary investigation of cardiac abnormality in human beings.

scholarly journals IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT TULANG PADA MANUSIA MENGGUNAKAN METODE FORWARD CHAINING

2019 ◽  
Vol 7 (1) ◽  
pp. 29-34
Author(s):  
Ferly Ardhy
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Programming Language ◽  
Bone Disease ◽  
Human Bone ◽  
Early Symptoms ◽  
The Public ◽  
Forward Chaining ◽  
Lack Of Knowledge

Bone disease is a condition that damages the skeleton and makes bones weak and vulnerable to fractures. The high disease is caused by ignorance and lack of knowledge about the disease. Therefore, an expert system was created to diagnose bone disease in humans. The method used in making this expert system is the forward chaining method, forward chaining method using the PHP programming language and MySQL database. The results of this study are the application of expert systems to diagnose human bone disease using a forward chaining method that can be accessed by the public at large to diagnose early symptoms of bone disease without limited distance and time used.

scholarly journals Rancang Bangun Sistem Pakar Mendiagnosa Penyakit Tanaman Kelapa Sawit Menggunakan Metode Bayes Berbasis Android (Studi Kasus : Perkebunan PTPN 4 Air Batu)

2018 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Muhammad Dedi Irawan ◽  
Muhammad Khairi Ikhsan Nasution
Keyword(s):  
Expert System ◽  
Palm Oil ◽  
Oil Palm ◽  
Good Method ◽  
Training Data ◽  
Cellular Phones ◽  
Conditional Probabilities ◽  
Bayes Method ◽  
Palm Fruit ◽  
Fruit Oil

Abstract - PT. Perkebunan Nusantara IV Air Batu (PTPN IV) is a government-owned oil palm plantation that is engaged in the production of palm fruit, oil palm plants will grow well and produce optimally if the plant is protected from disease. However, there is an imbalance where every year palm oil needs increase, while oil palm production decreases. This is due to lack of understanding of plantation assistants on the types of diseases found in oil palm plants which can cause continuous damage to oil palm plants. The Bayes method is one method that is suitable for selection, because the Bayes method is a good method in machine learning based on training data using conditional probabilities as the basis. With this expert system it is expected that plantation assistants can find out the type of disease and its solution quickly so that the problem of decreasing oil palm production can be overcome. The results of the research in the form of an expert system diagnose the disease of oil palm plants using the Android-based bayes method thus, this application can be used to analyze diseases using cellular phones. Keywords - Palm Oil Disease, Expert Systems, Bayes Method, Android.

scholarly journals Rancangan Aplikasi Sistem Pakar Diagnosa Penyakit Mononukleosis Dengan Metode Naive Bayes

2020 ◽  
Vol 7 (3) ◽  
pp. 403
Author(s):  
Rizky Hasanah Restari ◽  
Sinar Sinurat ◽  
Suginam Suginam
Keyword(s):  
Expert System ◽  
Health Center ◽  
Naive Bayes ◽  
Disease Diagnosis ◽  
Naïve Bayes ◽  
The Other ◽  
Daily Activities ◽  
Bayes Method ◽  
Other Hand ◽  
Naive Bayes Method

Health is one of the important factors for carrying out daily activities. However, some people do not care about the health of their bodies so that in the end many diseases that are diagnosed late cause the condition at a serious stage. One of the diseases in question is mononucleosis. In general, if the community is exposed to symptoms of mononucleosis, they will go to the nearest hospital or health center to do the examination. But on the other hand they have to sacrifice enough time for that. For this reason, it is necessary to make an application for a disease diagnosis expert system for the community as a means of overcoming these problems. With this design, an expert system of mononucleosis is produced, where this system uses the naive bayes method and the doctor's knowledge into the system. This expert system will produce output / output in the form of the diagnosis of mononucleosis

scholarly journals Sistem Pakar Diagnosa Virus Corona Dengan Metode Naïve Bayes

2021 ◽  
Vol 9 (1) ◽  
pp. 81
Author(s):  
Fareza Aditiyanto Nugroho ◽  
Arif Fajar Solikin ◽  
Mutiara Dwi Anggraini ◽  
Kusrini Kusrini
Keyword(s):  
Expert System ◽  
Natural Disaster ◽  
Naive Bayes ◽  
Virus Disease ◽  
Diagnostic System ◽  
Naïve Bayes ◽  
The Body ◽  
Human Being ◽  
Bayes Method ◽  
The World

Humans being are faced with non-natural disasters which have bad effect for population on the world. This non-natural disaster is called Corona Virus Disease (COVID-19). This COVID-19 will become a pandemic in 2020. This types of COVID-19 is coming from the Orthocronavirinae. It belongs to the Coronaviridae and the Nidovirales. This type of that virus has caused some disease to birds, mammals and also human being. Therefore, the research was conducted. The result of this research will give the information about system which related the classification human being according to their transmission to the body. This research used naïve bayes method. The result of this research is diagnostic system with the level of accuracy 94%. Thus, COVID-19 diagnostic expert system used to know the level of COVID -19 infections to human being. It can help the user knowing the next treatment.Keywords : Expert System, Naïve Bayes, Coronavirus, Covid-19

scholarly journals Tuberculosis Disease Diagnosis Expert System Method of Certainty Factor

2020 ◽  
Vol 2 (1) ◽  
pp. 129-134
Author(s):  
Betti Mastaria Br Sembiring ◽  
Paska Marto Hasugian
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
Disease Diagnosis ◽  
Certainty Factor ◽  
Disease Symptoms ◽  
System Method ◽  
Tuberculosis Disease Diagnosis ◽  
Tuberculosis Disease

Nowadays computers are widely used in the medical world to aid in the diagnosis of a disease. The most frequently encountered Penyakityang adalahpenyakitTuberculosis. Therefore, prevention of tuberculosis disease begins with diagnosing dini.Salah a technique in diagnosing tuberculosis disease is an expert system. Therefore research inibertujuan construct an expert system that is used for early diagnosis of Tuberculosis disease by gejalayang in anguish. The system displays the amount of credence to the possibility of disease symptoms yangdiderita users. The value of these beliefs using Certainty Factor, because the CF is able to determine the value of trust in a greater uncertainty and be able to demonstrate absolute confidence.

scholarly journals Expert System for Diagnosing Human Skin Diseases Using Web-Based Naïve Bayes Method

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Khoirunnisa devita Sari ◽  
Ade Eviyanti
Keyword(s):  
Expert System ◽  
Human Skin ◽  
Skin Disease ◽  
Skin Diseases ◽  
Naive Bayes ◽  
Expert Knowledge ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Web Based ◽  
Naive Bayes Method

Skin disease is a disease that often found in tropical countries like Indonesia. According to the survey, skin disease is the third of the ten most outpatient diseases. Lack of public knowledge about skin diseases and how to prevent and treat them can cause a person to develop acute skin diseases. The purpose of this research is to create an expert system application for diagnosis of human skin diseases using the web-based naïve Bayes method. With expert system, it hoped that human skin diseases can be detected early and can minimize the occurrence of more dangerous diseases. The calculation in this expert system uses the naïve Bayes method. This expert system makes diagnosis by analyzing input of symptoms experienced by patient and then processing it using certain rules according the expert knowledge that has been stored in the knowledge base. The result of this research is to build an expert system for diagnosing human skin diseases using website-based naïve Bayes. The results of the system trial of 20 respondents were the website could provide diagnosis results based on the inputted rules and could diagnose skin diseases properly. This website can used as an alternative use of technology so it can be used to diagnose skin diseases quickly, precisely and accurately. So in the future the handling of skin diseases can be faster and more efficient.

scholarly journals Expert System For Diagnosing Diseases In Children Under Five Uses Certainty Factor Based Websites

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Faiqotul Himma Ramadhanti ◽  
Ade Eviyanti
Keyword(s):  
Expert System ◽  
Medical Personnel ◽  
Certainty Factor ◽  
Children Under Five ◽  
Early Symptoms ◽  
Under Five ◽  
Factor Method ◽  
Lack Of Knowledge

Immunity in children under five is not as good and perfect as adult immunity. Therefore, children under five are susceptible to disease and easily contracted by adults. Lack of knowledge about the symptoms of a disease that attacks children under five can aggravate the situation and result in delays in treatment by medical personnel. Therefore, this expert system is made to make it easier for parents to recognize the symptoms of diseases that attack their toddlers. With this expert system, parents can find out the early symptoms of the disease that attacks their child. In making this expert system using a certainty factor method or a method that defines the measure of certainty of facts or rules to describe an expert's belief in the problem at hand. This expert system will diagnose the symptoms that the patient has previously selected. Then from the choice of these symptoms will be obtained using the value of expert confidence that has been stored in the knowledge. The results of this study were to build an expert system for diagnosing diseases in children under five using a certainty factor method based on a website. With this website, we can take advantage of today's technology to diagnose diseases in children under five. This website can make it easier for parents to consult because they can use it anywhere, effectively and quickly.

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