Bayes Theorem Method Research Articles

Expert System Diagnosing Heart Disease using Bayes' Theorem Method

Heart disease is one of the leading causes of death in Indonesia. The high number of deaths from heart disease is caused by the lack of cardiologists, the lack of public awareness of conducting regular heart health checks and the poor lifestyle of patients. So we need an application that can make it easier for users to detect heart disease early and independently. In this study, the aim is to build an application using the website-based Bayes Theorem method as a tool for diagnosing coronary heart disease. In this application, patients do not have to wait long for treatment by a doctor, but it can be an alternative to anticipate treatment quickly and precisely. How to use this application, the admin inputs questions in the form of symptoms that will be answered by the user, then the system will process all user answers using the Bayes theorem method and the system will issue output in the form of diagnostic results in the form of heart disease and various solutions. This application uses a Web programming language and Php & Mysql as a database. The system that has been built can assist patients in knowing the type of heart disease that is being suffered by the patient and according to the analysis of heart disease experts.

Expert System for Diagnosing Pests and Diseases on Onion Crops due to Climate Change and Weather using Bayes' Theorem Method

The main purpose of this study is to diagnose the types of pests and diseases on shallot plants due to climate change and weather carried out at the Department of Agriculture, Humbang Hasundutan district. Pests and diseases of shallot plants can be disturbed or infected by pests and diseases to other shallot plants so that farmers need to be wary of. Therefore, the dissemination of information about pests and diseases is very necessary to find out early on the types of pests and diseases in shallot plants due to climate and weather changes. Types of pests and diseases of shallots due to climate and weather changes are onion caterpillar (Spodoptera exiqua), leaf miner fly (Liriomyza chinensis), bodas pest (Thrips tabaci), purple spot (Alternaria porri), anthracnose (Cholletorichum gloesprorioiodes), dew , Mosaic disease or mole. So that it aims to produce an application-based expert system to diagnose pests and diseases on shallot plants due to climate and weather changes through the symptoms that occur in shallot plants. The methodology used for this research is the Bayes Theorem method. References from internet books and experts in their fields are Sumurung Toga Torop, who works at the Humbang Hasundutan Agriculture Service. As for the software using Visual Basic 2010 as its programming language, as well as Microsoft Access 2010.

Analisis Penyakit Tanaman Bawang Merah Menggunakan Metode Teorema Bayes

Shallot plants or in Latin Alliumascalonicum L is a horticultural plant that gets a lot of attention from both the public and the government. Over the past few years shallots are included in the top six vegetable commodities that are exported together with cabbage, cabbage or flower cabbage, chili, tomatoes, potatoes. Onion plants are very susceptible to disease that can strike at any time. Some diseases that can attack the onion plant include Onion Caterpillar Disease, Leaf Snorer Disease, Trip, Moler Disease, Trotol, Dew Feather and Anthracnose. In this study using the Bayes theorem expert system, each symptom has a density value to the disease which is then calculated using the formula of the Bayes Theorem Method and processed using certain rules and inference using Forword Chaining. This research is expected to help the onion farmers in diagnosing the disease so that it can reduce the material losses with less than 60%.

Expert System for Diagnosing Chicken Diseases using Bayes' Theorem

Chicken disease is a condition in which the organs of the chicken farm cannot function normally. To make a diagnosis of the disease requires further examination carried out by specialists (experts). An expert system is a system that uses human knowledge entered into a computer to solve problems that are usually solved by experts. The system created in solving the problem uses the Bayes theorem method where the inference process uses Forward Chaining. The application was developed using the Visual Basic 2010 programming language and MySQL database.

Expert System of Pest Diagnosis in Passion Fruit Plants using the Bayes Theorem Method

Purple passion fruit has the common name granadilla or passion fruit (English), passion fruit (Indonesian), including in the family Passifloraceae. It is estimated that there are 500 species of Passifiora in the Passidoraceae family, one of which is the form of edulis or purple forma known as purple passion fruit, which includes this form is acid passion fruit with purple fruit skin (purple) also called cucumber or purple passion fruit (P. Edulis f. Edulis Sims). Purple passion fruit passion fruit can only grow and develop well in subtropical and tropical highlands. This application is based on mobile with the Android operating system by utilizing the expert system of the Bayes Theorem method. With the Bayes theorem method implemented in the Application of control of passion fruit plants in order to make it easier to do an initial diagnosis without having to spend a lot of time calling a plant expert in the field of passion fruit plants. The characteristic of the Bayes Theorem method is that the Bayes Theorem is used to calculate opportunities in a hypothesis, by determining the probability value of the expert hypothesis and the evidence value obtained from the diagnosed object, then calculating the probability value. The expected results of this study are that applications can make it easier to find out the passion fruit pests and quickly provide countermeasures without having to take too much time to call or meet a plant expert and make it easier for users to use the android-based application.

Expert System Diagnose Disease Persian cat with Bayes Theorem Method

Lack of knowledge of the disease and the limitations Pesia cat disease management is often experienced by the owners of Persian cats. Therefore it is necessary to act / respond quickly to prevent infection with the disease more serius.Teorema Bayes is a method used to predict the probability. Therefore, in this study will be analyzed Persian cat disease data using Bayes theorem using four diseases areFeline Leukemia Virus, Worms, Cat Flu and Mushrooms Cryptococus. Based on these descriptions, we need a system that can represent an expert who has the knowledge base and experience of the Persian cat disease, which is an expert system. Developments in information technology more widely and rapidly. So much in use in various fields. That accompanied the information technology internet support each other resulting in increased web-based technologies

Expert System Diagnosing Disease of Honey Guava Using Bayes Method

Honey Guava Fruit (Green Guava Deli) is one of the fruit that are very popular, liked, and consumed by the people. The pProblems that cause a decline in the quality of guava due to honey guava plants can also be attacked by disease. The limited access information about honey guava disease is one of the obstacles, while the number of agricultural experts is still insufficient. In this study a media system will built with an expert system approach. The application development phase begins with the system analysis stage, namely data analysis and system requirements description, building a knowledge base, Data Flow Diagram, Entity Relationship Diagram, and creating a table structure, table design, and interface menu design. After the design phase is complete, it is continued to the implementation and testing phase of the application. This application uses Visual basic. Net as a programming language and Sql Server as a database. The research was conducted to make Honey Guava Disease Diagnosis System Expert System software that can work like an agricultural expert. The system is able to diagnose as many as 3 diseases using the Bayes Theorem method.

Expert System for Diagnosis Chicken Disease using Bayes Theorem

Chicken disease is a condition in which the body organs of chickens cannot function normally. Diagnosing a disease requires symptoms that appear on the chicken’s body. To conduct a disease diagnosis, further examination is needed by specialists (experts). An expert system is a system that uses human knowledge that is entered into a computer to solve problems that are usually resolved by experts. The system created in solving problems uses the Bayes Theorem method in which the inference process uses Forward Chaining. The application was developed using the visual basic 2010 programming language and MySQL database.

Bayes Theorem and Forward Chaining Method On Expert System for Determine Hypercholesterolemia Drugs

The development of technology capable to imitating the process of human thinking and led to a new branch of computer science named the expert system. One of the problem that can be solved by an expert system is selecting hypercholesterolemia drugs. Drug selection starts from find the symptoms and then determine the best drug for the patient. This is consist with the mechanism of forward chaining which starts from searching for information about the symptoms, and then try to illustrate the conclusions. To accommodate the missing fact, expert systems can be complemented with the Bayes theorem that provides a simple rule for calculating the conditional probability so the accuracy of the method approaches the accuracy of the experts. This reseacrh uses 30 training data and 76 testing data of medical record that use hypercholesterolemia drugs from Tugurejo Hospital of Semarang. The variable are common symptoms and some hypercholesterolemia drugs. This research obtained a selection of hypercholesterolemia drugs system with 96.05% accuracy

Penalaran Berbasis Aturan Untuk Diagnosa Awal Penyakit Anjing Menggunakan Teorema Bayes

Many pets can be played with, socialize and even live together with humans. Numbers of animal clinics have increased to provide care for pets. This study focuses on Dog as pet. Desease and improper treatment of dog will adversely affect the Dog. In dealing with the problem of Dog disease, Dog owners may experience difficulties due to limited number of clinics and veterinarians, especially in rural areas. As a solution, Artificial Intelligence is used by using expert systems that can help inexperienced medical personnel diagnose early symptoms of Dog disease. The search method used in this research is Forward Chaining and Bayes Theorem method to handle uncertainties that arised. Based on knowledge acquisition, 3 diseases were obtained with 38 simptoms and 60 cases. Based on the tests conducted then obtained the sensitivity value of 80%, the value of accuracy of 88.6% indicates that this expert system is able to diagnose dog diseasesKeywords: Dog, Expert System, Forward Chaining, Bayes Theorem.

SISTEM PAKAR MENDIAGNOSA PENYAKIT PADA UNGGAS DENGAN METODE TEOREMA BAYES BERBASIS WEB

Poultry has many benefits such as its eggs and meat that cannot be separated from the needs of daily consumption. However, there is a major problem that almost experienced every year for the breders. The disease in poultry is a serious problem that becomes obstacles for the breeders. Based on this problem, the application maker made an expert system application to diagnose the disease in poultry with Bayes theorem method. This application is expected to help the breeders in diagnosing the disease in poultry, therefore the death of poultry can be minimized. This application has been successfully designed and implemented using notepad ++ and php MySQL through several steps of main menu design system, those are; consultation, diseases, and aid. The coding making is done in notepad ++ application. Then making the database is done in php MySQL. The result reveals that this application is made to identify the disease based on the existing symptoms. In testing, 10 breeders stated that this application can help diagnose the disease in poultry.

An assessment of the use of Bayes' Theorem for forecasting in public health: the case of epidemic meningitis in China.

A mathematical model based upon Bayes' Theorem (BT) was used to forecast the occurrence of epidemic cerebrospinal meningitis (ECM) in ten communities in North China. Reports of ECM from each ten-day period during the meningitis season and records of special population movement during 1960-82 were analysed to establish forecast models. Calibration, split-sample, random-sample selection, as well as actual forecast tests, were used to check the efficiency of the models. For all the tests, the theoretical occurrence of ECM forecast by the BT method was compared with the observational data. Since the BT method offers efficiency and convenience, it is recommended for use in planning for the prevention and control of ECM in China.