Bayes Theorem Method Research Articles

Sistem Pakar Diagnosa Penyakit Akibat Virus Pada Manusia Menggunakan Metode Teorema Bayes

An expert system is a computerized application that aims to imitate the reasoning process of an expert in solving certain problems and making decisions or conclusions because their knowledge is stored in a knowledge base to process problem solving. The basis of an expert system is how an expert's knowledge is transferred to a computer and used to make decisions and draw conclusions based on that knowledge. Many expert system applications have emerged in the medical field. By answering questions on an application similar to consulting a doctor, this expert system allows ordinary people to detect diseases based on the symptoms they experience. In this way, lay people can also identify diseases and treatment solutions early, which allows for rapid treatment and disease prevention. This system aims to provide support to medical personnel in carrying out initial diagnoses, increasing diagnostic accuracy, and assisting in making medical decisions more quickly and efficiently. The use of the Bayes Theorem method allows the system to handle uncertainty and variations in the symptoms experienced by patients, so as to provide more accurate results.

Expert System for Diagnosing Cancer Using Bayes Theorem Method

Cancer is a dangerous disease that is not contagious and is caused by abnormal cells or tissues that can grow rapidly. The rapid development of this network will cause several complications of this disease which develop rapidly as well. Adam Malik General Hospital is one of the government hospitals that has complete facilities to treat cancer patients. Because it is a regionally centralized general hospital, each patient has quite a long queue when conducting consultations and treatment, this can result in physical fatigue in patients because it takes too long in the queue. To overcome these problems, we need a system that can provide information and detect early cancer diagnoses. So that the doctor can use the results of the diagnosis issued by the system so that it can be analyzed further. This of course can speed up the time the patient is in the examination, so that the treatment process can run effectively and efficiently. An expert system is a system that can store information from an expert, such as a doctor, for example. One of the methods that can be used is the Bayes Theorem method, which is a theory of probable conditions that calculates the probability of an event that depends on evidence. From the results of the trials that have been carried out, the results show that the patient suffers from cancer, namely breast cancer with a value of 81.60%.

Application of Forward Chaining and Rule-Based Reasoning Methods to Design an Expert System for Pregnant Women Disease Diagnosis in a Private Hospital

This research aims to discover how to create and implement an expert system for prenatal disease diagnosis. To prepare this study, the author employed several data collection techniques, including observation, interviews, and a literature review. The system to be designed was developed using an object-oriented paradigm and a Rapid Application Development (RAD) technique. Multiple development stages are involved in creating RAD, including requirement planning, workshop design, and implementation. Based on the study findings, it was discovered that the PHP programming language, MySQL database management system, Apache web server, UML tool, and RAD system development methodology were used to create an expert system for identifying illnesses in expectant mothers. The forward chaining method is used for this expert system, where the first stages are to create an inference tree and set rules. This system likewise computes the consistency test using the Bayes theorem method. With an 80% accuracy rate, SISPADIBU can be used as a diagnostic tool for disorders related to pregnancy. SISPADIBU can use the user-entered symptoms to present the diagnosis results. According to the survey results, 80% of users said that SISPADIBU was highly user-friendly, that the layout display was simple to use, and that it was constructive in educating users about pregnancy disorders.

Profession recommendation based on multiple intelligence for high school students

One of the problems students often face is the lack of understanding of their interests and talents which will cause confusion in making future study choices and career plans. Career selection is an expression of personality into the world of work followed by identification of certain occupational stereotypes. Eight intelligences according to dr. Howard Gardner is linguistic, logical, mathematical, visual spatial, musical, kinesthetic, interpersonal, intrapersonal, and naturalist. This research purpose is to develop a system that produces information and professional recommendations that are in accordance with multiple intelligences of prospective high school students using a combination of Bayes' theorem and weighted product (WP) method. User’s preference value is calculated using the Bayes Theorem method to give each multiple intelligence value which is a criterion. WP method calculation to find professions that match user preferences. Weight of each criterion needed in WP method is calculated by Rank Order Centroid method. WP calculation will produce a ranking of 3 professions according to the input from the user. From system testing results that compared to results from experts, an accuracy of 67.33% is obtained. Based on the accuracy value, it can be said that the accuracy level system is quite good.

Diagnosis of Parasitic Diseases in Animals Cat Using Bayes Theorem Method

Cats are one of the most popular pets in the world, including Indonesian people who like to keep cats as pets, and even become a hobby for cat lovers. Diseases that often attack cats are caused by parasites, namely worms and fleas. Parasites that attack cats are grouped into two, namely ectoparasites and endoparasites. expert system which is a computer program , which is able to store knowledge and rules like an expert . With the help of an expert system, someone who is lay or not an expert in a particular field will be able to answer questions, solve problems, and make decisions that are usually made by an expert . The Bayes Theorem method can be applied to diagnose parasitic diseases in cats based on input symptoms chosen by the users, the system can perform analysis based on predetermined rules or knowledge base. Based on the probability value of each symptom and disease that has been made, the system can diagnose parasitic diseases in cats with different accuracy results, the highest value or percentage which is the result of the diagnosis of the parasitic disease. From the results of trials conducted by the expert system for diagnosing parasitic diseases in cats using the Bayes Theorem method, the highest value was obtained, namely the type of parasitic disease Flea Disease (P03) with a percentage of 38.66%.

Sistem Pakar Identifikasi Penyakit Kulit Melanoma dengan Metode Teorema Bayes

Melanoma is a skin cancer disease that occurs due to abnormal growth of melanocytes, which are cells that can produce pigment in the skin. Melanoma is one of the most vicious skin cancers and can easily spread to other organs in the human body, such as the lungs and brain. This expert system for diagnosing melanoma skin disease is a computer-based system that is used as a tool for diagnosing melanoma skin disease based on a dynamic knowledge base. The purpose of this research is to build an expert system that can identify Melanoma Skin Disease. An expert system built using the Bayes theorem method in a diagnostic process based on expert knowledge or experience. The results of this study present an expert system capable of diagnosing melanoma skin disease quickly, precisely and accurately. These results are presented in a system built in the form of a website using PHP programming with a MySQL database. Overall this expert system can be useful for patients or the general public to be able to know clearly about melanoma skin disease from the symptoms and can provide solutions in handling it.

Sistem Pakar Diagnosis Penyakit Tanaman Padi Dengan Metode Teorema Bayes

One of the cultivated plants is rice, oryza sativa in Latin, although some varieties are wild rice. Rice cultivation began in Indonesia around 15000 BC, although it is thought to have originated in India or Indochina. Rice is the most important crop in agrarian countries like China, India, Bangladesh and Indonesia. The japonica and indica groups usually contain rice plants. According to archaeological evidence, japonica rice was first domesticated around 9,000 years ago in the Yangtze Valley in southern China. Meanwhile, around 5,000 years ago, indica rice was first grown in the Ganges River valley. Rice-producing grass plants fall into this category. For most Indonesians, rice is a staple food. At the time of growth, rice plants are susceptible to various diseases which cause farmers to fail to harvest. To find out the diseases that attack rice plants, an expert who can diagnose rice plant diseases is needed. An expert is someone who understands the problem of diagnosing a disease. However, the lack of agricultural officers/extensioners in the Seputih Banyak District area. The purpose of this research is to apply an expert system using the Bayes theorem method to overcome problems regarding rice plant diseases and the limitations of agricultural officers/extensioners. And can be accessed by farmers anywhere when they need an epert system to diagnose a disease that attack rice plants without having to need assistance from extension agricultural extension officers.

Identification Types Of Student Learning Modalities In Physics Subjects With Expert Systems Using Bayes Theorem Method

Learning modality is a person's way of absorbing and processing information effectively and efficiently. This study aims to determine the results of the identification types of student learning modalities in physics subjects with an expert system using the Bayes theorem method, and the accuracy of the Bayes theorem method in identifying types of student learning modalities in physics subjects. This study uses the Bayes theorem method because it can produce a parameter estimate by combining information from the sample and other information that has been previously available to determine the results of the learning modality. This study uses 21 characteristics of learning modalities, 3 types of learning modalities, and 30 test cases obtained from an expert physics teacher at SMA Sumsel Jaya Palembang. Based on the tests that have been carried out, the results show that the system has an accuracy of 90% in identifying types of student learning modalities in physics subjects. It can be concluded that the Bayes theorem method can be used to identify types of student learning modalities in physics subjects.

EXPERT SYSTEM APPLICATION FOR DIAGNOSIS OF DENTAL DISEASES BASED ON WEBSITE USING BAYESIAN THEOREM METHOD

Teeth are small parts located in the upper or lower jaw. Each tooth is embedded in the gums, with its roots penetrating the gum line and entering the jawbone. The total number of teeth in the upper and lower jaw is 32. Teeth are divided into five types, each with a different function. Maintaining dental health is very important, as there are various dental diseases caused by leftover food consumed. Therefore, researchers have developed a system for diagnosing dental diseases by collecting symptoms that have been gathered through interviews with experts and patients, as well as collecting journals related to teeth. Then, all the data is entered into the application to determine the probability of the patient having a certain type of dental disease using the Bayes Theorem method.

Penerapan Metode Teorema Bayes Dalam Mendiagnosa Penyakit Tubercolosis

In human life, health is the most valuable asset. a healthy body and soul gives happiness to everyone. But sometimes circumstances make human health decline. One of the causes of declining human health is due to viruses or bacteria that spread without people knowing it. One of the infectious diseases is tuberculosis (TB). Tuberculosis is a disease that occurs due to an infection caused by a bacterium called Mycobacterium tuberculosis. TB is a disease that spreads very easily, namely by air. The patient will spread germs through the air if the patient coughs or sneezes. Death is not uncommon because those with symptoms are afraid to go to the hospital for medical check-ups because they are hampered by a lack of funds. This situation is very concerning. Because of these circumstances, technological developments can be used as an alternative solution in replacing or assisting in diagnosing diseases experienced by people based on their symptoms. One of the technologies that develop about diagnosing disease is by using an expert system. An expert system is a system created by experts by developing technology based on science. In expert systems, their use must be combined with a method so that they can work properly and optimally. In this study the method used is the Bayes Theorem method. The Bayes Theorem method was developed by a priest named Thomas Bayes. The pastor comes from England who is a Presbyterian pastor. The Rev. Thomas Bayes developed Bayes' Theorem in 1763 and was perfected and redeveloped by an expert named Laplace. Based on the results of the above process, information was obtained that 87% of patients who consulted had pulmonary tuberculosis

WASTE MATERIAL ANALISYS WITH THE IMPLEMENTATION OF LEAN CONSTRUCTION

Waste material affects project implementation. In addition, it also affects the productivity of the project as well as costs and time. Based on this, good management is needed in handling and minimizing the occurrence of material waste. Lean Construction is one approach that can be used to handle and minimize this occurrence. This study aims to determine the most dominant waste material indicators that cause material waste, determine the estimated costs resulting from material waste and total cost estimates until the observed work is completed, determine the most dominant type of material that causes material waste and determine the percentage of Lean Construction implementation. The case study of this research was conducted on the Karangsambung Indonesia Geodiversity Area Facility Development Project Package 2. The Bayes theorem method was used to determine the most dominant indicator of material waste that causes material waste to occur. Pareto diagrams are used to determine the most dominant type of material that causes material waste. The data from this study were obtained by conducting interviews, observations and filling out the waste material questionnaire and the Lean Construction application questionnaire. The conclusion of this study is that the most dominant indicators that cause material waste are Defect and Waiting with a confidence value of 100% each. The estimated cost obtained during the 2-week observation is Rp. 10,440,859.91 and the estimated cost until the work is completed is Rp. 26,102,149,77. The most dominant type of material that causes material waste is deformed reinforcement Ø22 (Rp. 4,436,673.32), deformed reinforcement Ø 19 (Rp. 2,051,606 ,29) and threaded reinforcement Ø 16 (Rp. 1,387,546,88). The percentage of Lean Construction implementation obtained is 98.94%.

Sistem Pakar Diagnosa Penyakit Pada Perokok menggunakan Metode Teorema Naive Bayes

The purpose of this research is to produce an expert system for diagnosing disease in smokers using the Naïve Bayes Theorem method. The problem that arises in this study is the process of determining the disease in smokers through the diagnosis of experts, patients must come to the hospital and see a doctor during working hours. In the development of this expert system using the waterfall SDLC method with the stages of Analysis, Design, Coding, Testing, and testing methods carried out in this Blackbox research. To determine the type of smoker's disease, this system uses the PHP MySQL Database programming language, and Dreamweaver uses. The results of this study are in the form of a website-based expert system that is able to help users or the public in diagnosing passive smoking and providing formations about smoking diseases. The results of the Blackbox Testing test have an average score of 4.2 with a valid category

Expert System to Diagnose Eye Disease Due to Frequently Using Computer with Bayes Theorem Method

Eye disease due to frequent use of computers is one of the dangerous diseases in health because if not treated quickly it will result in blindness. These eye diseases can be diagnosed through the symptoms that arise in humans or through their clinical picture, through these symptoms an expert system can be made to make a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The expert system made in carrying out the diagnosis uses the Bayes theorem method to calculate the probability of an event occurring based on the influence obtained from the results of observations and experts. The system was built using PHP and MySQL programming as a database. The method used for tracing is Bayes' theorem. While the results of the diagnosis will inform about the results of the diagnosis containing a list of symptoms entered, information on the results of the rules regarding the eye disease suffered and information about possible treatments that can be carried out as well as treatment solutions.

Web-Based Expert System for Diagnosing Gastric Disease Using Bayes Theorem Method

Health is a very expensive thing, so it takes an awareness to protect it. The human body has many limbs, one of which is the stomach. Gastric disease is a disease that cannot be accommodated, because if left untreated it can cause other diseases to arise and can also cause death if it is not immediately supported. Gastric disease can be caused by an inappropriate diet, a burden on the mind and also an infection caused by bacteria. The author took the initiative to create a web-based gastric disease diagnosis expert system using the Bayes theorem method which is useful for gastric disease sufferers in diagnosing their own gastric disease. The method used by researchers is the Bayes theorem method. The data collection technique used is quantitative data techniques. The results that have been achieved from this research are that it can prevent and minimize the risk of gastric disease in sufferers or the community.

Expert System for Diagnosing Liver Disease Using Web-Based Bayes Theorem Method Metode

Many people still do not know the risks, prevention, and treatment solutions related to liver disease. Therefore, many Indonesian people are affected by liver diseases such as hepatitis and other liver diseases because they are not aware of the symptoms they are experiencing. Therefore, this expert system is designed to help diagnose the symptoms experienced by people or patients who have liver disease. With this expert system, it can help overcome delays in handling so that it is not severe later. This expert system is created using the Bayes theorem method where in each symptom there is a probability or possibility which then gets the final result in the form of how big the event occurred. This expert system diagnoses the symptoms selected by the patient. After that, get the value of the possibility of a disease suffered by the patient. The results of this study are to produce an expert system for diagnosing liver disease using the website-based Bayes theorem method. This system can help diagnose a patient’s symptoms quickly and is used anywhere.

Sistem Pakar Mendiagnosis Penyakit Pada Ayam Broiler Menggunakan Metode Teorema Bayes Berbasis Web

The need for chicken cannot be denied in Indonesian society, especially in the consumption of eggs and chicken meat so that it will affect economic growth. To produce healthy meat and eggs free of disease, breeders must pay attention to the health of their pet chickens. Starting from providing rations, vaccination and cage maintenance. Chicken disease is very susceptible to cage cleanliness and consumption of the food given. As for the scope of the problem in this study, namely disease in broiler chickens. The system used is a web-based expert system with the Bayes Theorem method. By applying the Bayes theorem method to expert systems in diagnosing broiler disease and designing an expert system application in determining broiler disease. Aims to assist breeders in dealing with diseases specifically broiler chickens and add to the list of references in applying the Bayes Theorem method to expert systems. Using testing with the PHP MYSQI application with the supporting tools.

Sistem Pakar Mendiagnosa Penyakit Keputihan Pada Wanita Dengan Metode Teorema Bayes

Leucorrhoea is a discharge other than blood from the vaginal canal, if abnormal vaginal discharge is left untreated, as a result the infection can spread, enter the uterus, fallopian tubes, and can infect the ovaries. The application of an expert system in the health sector will greatly assist in survival someone. Expert systems can help diagnose a type of disease based on their own symptoms quickly and precisely. An expert system that is designed as a tool to diagnose the type of leucorrhoea, especially in women who experience vaginal discharge, but often they feel able to recognize themselves that they are suffering from vaginal discharge without feeling the need to go to a doctor for a more detailed examination, and only treat themselves with medication. Free-sale vaginal discharge medication. This expert system will display a selection of symptoms that can be selected by the user, then get the final result with the Bayes theorem method by providing a diagnosis result in the form of a probability value for the emergence of each type of disease and solution. Expert system applications are built on a web basis using HTML, PHP, CSS using the mysql database.

Implementation of the Bayes theorem method for identifying diseases of children under five

Disease is very susceptible to occur in children under five because the immune system in children under five has not been fully developed. Lack of knowledge about the diseases of children under five and the symptoms they experience makes parents fearful. The lack of knowledge of children's diseases from experts can result in delayed treatment. Problems that occur can be overcome by utilizing artificial intelligence technology. One of the artificial intelligence technologies is an expert system. Information needs very quickly from an expert to deal with problems or diseases of children under five that are expected by parents or society. So that is what drives the development of a software application, namely an expert system for the identification of diseases of children under five. An expert system for the identification of toddlers' diseases is made as a tool to diagnose diseases experienced by toddlers by using the symptoms experienced by toddlers as a tool to detect diseases experienced by children under five. The system can identify 5 types of disease with 23 symptoms of disease. This expert system uses the development method of problem identification, system design, implementation and testing. Inference in this expert system uses the Bayes theorem method. This system is built with Visual Basic and Microsoft Access as the database. The results of consulting tests with this system show that the system is able to determine the disease along with the initial treatment and treatment solutions that must be carried out, based on the symptoms previously selected by the user.

Lithofacies classification using Bayes theorem method : Case study Western Desert, Egypt

This paper shows the availability of using the Bayesian classification method to predict class membership probabilities in one of the deep tight reservoirs in Western Desert, Egypt. The workflow of our project that using the Bayesian method used the deterministic petrophysical results of three training wells to train the data and extract the classifiers. The classified data were modeled using Gaussian distribution for each lithofacies. The used wells were acquired from a deep Jurassic gas reservoir in the Western Desert of Egypt. The fitting between actual and modeled data has been reached by minimizing the L2 norm. Besides, a cross-validation process was used for validating the resulted classifiers. Finally, the Bayesian classification method can predict the GWC with an accuracy of 4 m. To avoid probability interference caused by the compacted shale more data should be added to the initial model.

Sistem Pakar Untuk Diagnosis Hama Pada Tanaman Jambu Air Menggunakan Metode Theorema Bayes

Technology is a tool or means used by humans to make ends meet. Technological development covers various aspects of life, such as health, education and in agriculture. One of the uses of current technological developments is the creation of expert systems. Expert systems in agriculture can help farmers in overcoming problems in their crops based on the symptoms that occur in these plants, so farmers can quickly find the right solution. One type of agricultural plants that are susceptible to various pests is water guava. In resolving pests and diseases that attack not a few of the farmers or owners make mistakes in overcoming the problems encountered. So by making an expert system to diagnose guava plant diseases it is expected to help farmers to overcome problems by providing good solutions. The process of making this expert system uses the Bayes theorem method. Bayes theorem method is one method to overcome the uncertainty of data. Where this method is based on the initial condition where the initial condition is a condition of existing symptoms then subject to predetermined rules then the greatest truth value is taken to determine the conclusions and solutions of the symptoms that have been mentioned previously.