PENERAPAN METODE CERTAINTY FACTOR DALAM MENDIAGNOSA PENYAKIT CACAR PADA KULIT MANUSIA

2019 ◽  
Vol 3 (1) ◽  
pp. 10-22
Author(s):  
Eferoni Ndruru
Keyword(s):  
Expert System ◽  
Respiratory Tract ◽  
Severe Asthma ◽  
Allergic Disease ◽  
Skin Disease ◽  
Allergic Diseases ◽  
Human Science ◽  
The Body ◽  
Certainty Factor ◽  
Allergic Skin

Expert system is a method used to implement human science to computer systems with the aim of solving a problem in the field of knowledge. Allergic disease is an overreaction from the body to certain particles from outside that enter the body which makes people feel uncomfortable and disturbed, allergies can occur with a variety of symptoms, some have experienced mild symptoms such as itchy eyes, sneezing, or reddened skin, and some are suffering from allergies with severe asthma. Factors from the causes of this allergy are very much encountered such as through the respiratory tract, through food, through drugs and so forth. Medical experts can use the application that has been built, which aims to make it easier to diagnose allergic diseases of the skin by only paying attention to the symptoms experienced. By using the Certainty Factor (CF) method, we get the value of a person's likelihood of developing allergic disease or not. The Certainty Factor (CF) method is very beneficial for the allergic skin disease system. Keywords: 3-5 Expert Systems, Skinpox, Certainty Factor.

Situsparu: Sistem Pakar Untuk Deteksi Penyakit Tuberkulosis Paru

2018 ◽  
Vol 10 (1) ◽  
pp. 41-47
Author(s):  
Ricky Surya ◽  
Dennis Gunawan
Keyword(s):  
Expert System ◽  
Tuberculosis Patient ◽  
The Body ◽  
Certainty Factor ◽  
Good Reliability ◽  
Delone And Mclean ◽  
The World ◽  
Index Terms ◽  
Manual Calculation ◽  
Tuberculosis Prevalence

Tuberculosis is an infectious disease caused by mycobacterium tuberculosis. It can affect some parts of the body: lungs, lymph nodes, intestines, kidneys, endometrium, bones, and brain. According to the survey of tuberculosis prevalence conducted by Republic of Indonesia Ministry of Health in 2013-2014, Indonesia was the second country in the world with the most case of tuberculosis. It makes Indonesia become a country with emergency in lungs tuberculosis. An expert system for lungs tuberculosis detection is built to help people detecting the possibility of suffering from lungs tuberculosis. Therefore, it is hoped that the lungs tuberculosis patient can have early treatment. Certainty factor is used to solve the uncertainty problem delivered by the doctor when examining the patient. Thus, certainty factor is an appropriate method to be used in the expert system for detecting certain disease. This method has been correctly implemented, proved by comparing system detection result to manual calculation result. The expert system has 81.25% accuracy, 83.49% success using DeLone and McLean model, and a cronbach alpha of 0.82 which indicates a good reliability based on the indicators used in the questionnaire. Index Terms— Certainty Factor, Disease Detection, Expert System, Pulmonary Tuberculosis, Situsparu

scholarly journals Aplikasi Diagnosa Granulomatous Dermatis Menggunakan Certainty Factor

2019 ◽  
Vol 3 (2) ◽  
pp. 78
Author(s):  
Puji Sari Ramadhan
Keyword(s):  
Artificial Intelligence ◽  
Factor Analysis ◽  
Expert System ◽  
Mycobacterium Leprae ◽  
Final Diagnosis ◽  
The Body ◽  
Limited Information ◽  
Certainty Factor ◽  
Granulomatous Dermatitis ◽  
Reference Tool

Granulomatous dermatitis is a type of inflammatory disease in the inner layer of the skin that causes damage to the nerves, skin layers and motor members of the body. This disease originated in the attack of an aerobic type of mycobacterium leprae which can spread and transmit infection by contact and air, besides this disease is estimated to enter Indonesia in the early V century. At present the diagnosis and treatment of Granulomatous Dermatis is experiencing difficulties, this based on the limited information and lack of knowledge of the community about Granulomatous Dermatis so that later it will result in late or unpreparedness of treatment in patients with Granulomatous Dermatis cases. On the basis of these events, it is very necessary to build a system by acquiring scientific concepts of artificial intelligence that are capable of producing an Expert System which can later be used to diagnose Granulomatous Dermatis by applying the Certainty Factor analysis. With the application of this diagnosis later can help the community and medical experts in diagnosing Granulomatous Dermatis as a reference tool in concluding the final diagnosis.

scholarly journals Characteristics of childhood allergic diseases in outpatient and emergency departments in Shanghai, China, 2016–2018: a multicenter, retrospective study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuanyuan Qi ◽  
Peng Shi ◽  
Renjie Chen ◽  
Yufeng Zhou ◽  
Lijuan Liu ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Tract Infection ◽  
Respiratory Tract ◽  
Respiratory Tract Infection ◽  
Emergency Departments ◽  
Outpatient Care ◽  
Skin Diseases ◽  
Allergic Diseases ◽  
Age Group ◽  
Allergic Skin

Abstract Background The prevalence of allergic diseases (ADs), such as asthma and allergic rhinitis (AR), is increasing worldwide in both adults and children. Although ADs are common and frequently coexist in outpatient care, city-level data regarding the characteristics of childhood AD remain limited in China. This study aimed to assess the profile and characteristics of ADs in the city of Shanghai. Methods A multicenter retrospective study was designed to collect routine administrative data from outpatient and emergency departments from 66 hospitals in Shanghai, China, from 2016 to 2018. Children with asthma, AR, allergic conjunctivitis (AC), and allergic skin diseases were investigated. Demographic characteristics, patients visit pattern, spectrum of diagnosis, and comorbidities were analyzed. Results A total of 2,376,150 outpatient and emergency visits for ADs were included in the period from 2016 to 2018. Allergic skin diseases accounted for 38.9%, followed by asthma (34.8%), AR (22.9%), and AC (3.3%), with a male predominance in all four diseases. Asthma and allergic skin diseases were most frequent in the 1 to < 4 years of age group, while AR and AC were more common in the 4 to < 7 years of age group. Asthma accounted for the greatest number of annual and emergency visits. The most frequent comorbidity of asthma was lower respiratory tract infection (LRTI) (49.3%), followed by AR (20.5%) and upper respiratory tract infection (14.1%). The most common comorbidities of AR were otitis media (23.4%), adenoid hypertrophy/obstructive sleep apnea (22.1%), followed by LRTI (12.1%), asthma (9.4%) and chronic pharyngitis (8.9%). Conclusions Asthma and allergic skin diseases were the most common ADs in outpatient and emergency departments in the study period. Respiratory tract infection was the most common comorbidity of asthma in children. More attention should be devoted to the treatment of comorbidities to improve childhood AD outcomes with a better understanding of the characteristics of ADs in outpatient care.

scholarly journals Perancangan Sistem Pakar Untuk Mendiagnosa Penyakit Diabetes Mellitus Menggunakan Metode Certainty Factor Design Expert System for Diagnosing Diabetes Mellitus Using Certainty Factor Method

CCIT Journal ◽  
2018 ◽  
Vol 11 (2) ◽  
pp. 182-191
Author(s):  
Musthofa Galih Pradana ◽  
Bondan Wahyu Pamekas ◽  
Kusrini Kusrini
Keyword(s):  
Diabetes Mellitus ◽  
Expert System ◽  
System Design ◽  
Design Process ◽  
Interface Design ◽  
Medical Personnel ◽  
The Body ◽  
Design System ◽  
Certainty Factor ◽  
Prevention Of Diabetes

Diabetes mellitus is a chronic metabolic disorder caused by the pancreas that does not produce enough insulin, so the body works to be disturbed. But by knowing the symptoms that exist, prevention of diabetes mellitus disease can be done as early as possible with the help of expert systems.One method of expert system used to diagnose symptoms of Diabetes Mellitus is Certainty Factor. The process undertaken in this research starts from literature studies, system design, system implementation and the last is testing the system. In the system design process is done by designing the database required by the expert system and also design the system interface design. After the design process is done then the next step is to implement the design into an expert system application. By using this method, the system gives results of possible symptoms experienced, presentation of beliefs, and treatment solutions based on the facts and the value of confidence given by users in filling out questions that have been given by the system.The results of this system are used to help medical personnel and patients in order to identify the symptoms of diabetes mellitus

scholarly journals Implementation Of K-Nearest Neighbor - Certainty Factor For Expert System Detection Of Idiopathic Thrombocytopenic Purpura

2021 ◽  
Vol 328 ◽  
pp. 04009
Author(s):  
Eva Y. Puspaningrum ◽  
Budi Nugroho ◽  
Dwi Putri Safira
Keyword(s):  
Expert System ◽  
Idiopathic Thrombocytopenic Purpura ◽  
Nearest Neighbor ◽  
Autoimmune Disorder ◽  
The Body ◽  
K Nearest Neighbor ◽  
Certainty Factor ◽  
Thrombocytopenic Purpura ◽  
Parameter Values ◽  
Test Scenarios

Idiopathic Thrombocytopenic Purpura (ITP) is an autoimmune disorder. ITP can occur in children and adults. This disease can be fatal because the platelet count is low due to the destruction of excessive platelets so that it can interfere with vital organs and bleeding occurs. The lack of knowledge of ordinary people about ITP disease, so many people assume that bruises and nosebleeds on the body are caused by fatigue. For that, we need a system that can imitate the expertise of an expert in diagnosing this disease based on the symptoms felt. The method used to support the expert system is the K-Nearest Neighbor and Certainty Factor methods which are a combination of 2 methods, where the classification results from the K-Nearest Neighbor method will be given a certainty value by the Certainty Factor method so as to produce a prediction. The results of combining the two methods can produce certainty in the diagnosis. Based on the test results using 3 test scenarios using parameter values k=3, k=5, k=7 and the results obtained the highest accuracy value with parameter value k=7 obtained an accuracy rate of 90,9%.

scholarly journals SISTEM PAKAR BERBASIS LOGIKA FUZZY UNTUK DETEKSI LEVEL PENYAKIT SCABIES

CCIT Journal ◽  
2017 ◽  
Vol 10 (2) ◽  
pp. 186-196
Author(s):  
Muhamad Safi’i ◽  
Hanny Haryanto
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Skin Disease ◽  
Direct Contact ◽  
Disease Diagnosis ◽  
The Body ◽  
Infected Person ◽  
History Of ◽  
Short Time

Scabies is a skin disease that is easily transmitted, either through direct contact or through intermediaries such as clothes, bed sheet, and water. The disease causes itching on the body, especially at night. Transmission of the scabies disease is very fast and can develop into an outbreak in a community. Obstacles that occur in the treatment of this disease is not all people with the disease could check it for a variety of reasons, such as too busy with work and economic limitations. This research using fuzzy Tsukamoto to develop an expert system for the detection of scabiesdisease. The use of expert systems is very important because it can be a tool to substitute the expert, the expert system is easy to use, and can make decisions in a short time. Scabies disease diagnosis process carried out by way of input symptoms  that suffered by patients. Symptoms that are used as input is a scratchy, itchy location, number of lesions or spots, and an extensive history of itching or the number of infected person. The outcome of this process is the level of scabies from mild to severe

scholarly journals HEMATOLOGICAL AND BACTERIOLOGICAL PREDICTORS OF OCCUPATIONALLY AND INDUSTRIAL CONDITIONED DISEASES IN MEDICAL WORKERS

2020 ◽  
Vol 99 (1) ◽  
pp. 125-128
Author(s):  
L. M. Karamova ◽  
Natalya V. Vlasova ◽  
L. G. Gizatullina ◽  
L. M. Masyagutova
Keyword(s):  
Respiratory Tract ◽  
Allergic Diseases ◽  
The Body ◽  
Hospital Environment ◽  
Upper Respiratory Tract ◽  
Hemoglobin Content ◽  
Hematological Indices ◽  
Mucous Membranes ◽  
Upper Respiratory ◽  
Medical Examinations

Introduction. Medical workers in the process of labor are exposed to a complex of adverse factors: neuro-emotional, physical stress of a chemical, physical and biological nature. A long stay in a hospital environment with medical workers can lead to the formation of various diseases of microbiological etiology or the carriage of pathogenic and conditionally pathogenic flora and the development of dysbiosis. Objective. Give hematological and bacteriological characteristics of the health status of medical workers. Material and methods. The results of laboratory studies of blood and mucous membranes of the upper respiratory tract of medical workers performed during the performing occupational medical examinations are analyzed. Results. Hematological indices were found to be characterized by an increased hemoglobin content in one-fourth of the examined workers, as well as lymphocytosis, eosinophilia, cholesterolemia. The microflora of the mucosa of the upper respiratory tract is mainly represented by Staphylococcus aureus, Candida albicans, Streptococcus pyogenes in 65.2% of the workers; the remaining 34.8% were revealed to have a resident microflora. With the experience of work, the frequency of insemination increases and doubles by 10 years of the work. The structure of microflora is also changing. In the nosological form of occupational morbidity, allergic diseases prevail and account for 60.8%, tuberculosis - 26.0%, and hepatitis - 8,6%. Conclusion. All these changes in the body are the basis of pathogenetic manifestations in the formation of allergic and pathogenic pathologies, which make up to 70.0% of all occupational morbidity.

scholarly journals Diagnose Disease Expert System Respiratory Tract Infection Method Using Certainty Factor

2020 ◽  
Vol 2 (2) ◽  
pp. 263-267
Author(s):  
Aritana Lahagu ◽  
Erwin Panggabean
Keyword(s):  
Expert System ◽  
Tract Infection ◽  
Respiratory Tract ◽  
Respiratory Tract Infection ◽  
Respiratory Tract Infections ◽  
Certainty Factor ◽  
Factor Method ◽  
Microsoft Access ◽  
Weight Calculation ◽  
Tract Infections

Respiratory tract infections are infectious diseases that interfere with the process of human breathing. When the breathing process takes place, there are often various kinds of diseases, most of which can only be treated by a lung specialist. The arrival of a pulmonary specialist for consultation can take hours and is expensive. Then we need an expert system that can quickly find out the type of disease in human breathing and how to handle it and the solutions that will be provided. Expert system is a system that uses human knowledge to find out the system that is entered into a computer and then is used to solve problems that usually require expertise or human expertise. One application of an expert system to diagnose respiratory tract infections is to use the certainty factor method. The certainty factor method is a method used to solve problems from uncertain answers, and also produce uncertain answers. This uncertainty is influenced by two factors, namely uncertain rules and uncertain user answers. The research aims to build an expert system application for handling respiratory tract infection problems with Visual Studio 2010 as a tool for designing applications and using Microsoft Access 2007 Database as a database. This expert system is able to calculate similarity in weight calculation based on symptoms of respiratory tract infection using certainty factor methods and provide reports using crystal reports

scholarly journals Using of topical bacterial lysates in modern clinical practice

2021 ◽  
pp. 49-56
Author(s):  
V. M. Svistushkin ◽  
G. N. Nikiforova ◽  
A. V. Zolotova ◽  
V. A. Stepanova
Keyword(s):  
Respiratory Tract ◽  
Inflammatory Diseases ◽  
Human Microbiome ◽  
Allergic Diseases ◽  
The Body ◽  
Economic Consequences ◽  
Medical Community ◽  
Side Reactions ◽  
Upper Respiratory Tract ◽  
Bacterial Lysates

Acute and chronic infectious and inflammatory diseases of the upper respiratory tract occupy a leading position in the structure of the pathology of the world’s population and remain the most frequent reason for patients seeking medical care. The prevalence and frequency of this disease in this nosological group makes a decisive contribution to the structure of the causes of temporary disability, which entails significant negative social and economic consequences. In this aspect, the spread of resistance of pathogens to etiotropic drugs and the insufficient arsenal of pathogenetic drugs stimulate the medical community to search for alternative approaches to the treatment of patients with respiratory pathology. One of these therapeutic areas is the use of immunomodulators, the most commonly used group of which are bacterial lysates. In the modern literature, sufficiently convincing data have been accumulated on the effectiveness of the use of bacterial lysates of systemic action, as a result of which the immune cells of the gastrointestinal tract are activated, which in turn leads to the restoration of autoregulation of the immune response throughout the body, and a decrease in the frequency of infectious and allergic diseases. The latest developments of domestic pharmacologists are topical bacterial lysates, the principle of which is based on the local activation of mucosal immunity in the respiratory tract. The undoubted advantage is that bacterial lysates, with all their effectiveness, do not harm the human microbiome, practically do not cause side reactions, combine well with other drugs, and can also be used at any stage of the disease, including for prophylactic purposes.

Sistem Pakar Diagnosis Penyakit Jamur pada Manusia Menggunakan Input Suara Berbasis Android

2019 ◽  
Vol 3 (3) ◽  
pp. 435-442
Author(s):  
Feriantano Sundang Pranata ◽  
Jufriadif Na’am ◽  
Sumijan
Keyword(s):  
Expert System ◽  
Early Detection ◽  
Skin Disease ◽  
Skin Diseases ◽  
Initial Diagnosis ◽  
Test Results ◽  
Certainty Factor ◽  
Early Diagnose ◽  
The Tropics

Fungal skin disease is a type of disease that is often suffered people in the tropics. Phenomena in the community often assume that this disease will heal by itself. However, if left the effects of fungal skin disease can worsen the sufferer condition. The importance of early detection and treatment is very necessary, but this requires patients go to hospital or doctor so that patients spend a lot of time and money. For this reason, was build an android expert system with speech to early diagnose fungal skin diseases. From this initial diagnosis will save time and money and provide alternative prevention for sufferers. The method used in this study is the Certainty Factor of 20 patients. The accuracy of the test results to the system compared to the results of the doctor's diagnosis is 95%. So that, this expert system can be an early alternative in diagnose fungal skin diseases in humans.

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