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 Penerapan Metode Certainty Factor dalam Sistem Pakar Pendeteksi Resiko Osteoporosis dan Osteoarthritis

2016 ◽  
Vol 7 (2) ◽  
pp. 59-69
Author(s):  
Stephanie Halim ◽  
Seng Hansun
Keyword(s):  
Expert System ◽  
Certainty Factor ◽  
Factor Method ◽  
A Value ◽  
Index Terms ◽  
Event Based ◽  
Wrong Action

Osteoporosis    is    commonly    referred    to “thinning” and osteoarthritis referred to “calcification”, but people giving wrong action treatment of these two diseases. Therefore, the aim of this study is to develop an android-based application to identify the risk of osteoporosis and osteoarthritis. To identify that risk was processed using certainty factor method. Certainty factor method related about event based on facts, which the source of those facts are from expert and assumed with a value, called certainty factor. From the testing result, the accuracy of this expert system is about 80%. Index Terms - Certainty factor, disease diagnose, expert system, osteoarthritis, osteoporosis

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 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%.

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.

scholarly journals Sistem Pakar Diagnosa Penyakit Tanaman Rambutan dengan Metode Forward Chaining dan Certainty Factor Berbasis Android

2020 ◽  
Vol 5 (3) ◽  
pp. 329
Author(s):  
Bayu Abrianto Risnadi ◽  
Fauziah Fauziah ◽  
Ratih Titi Komala Sari
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Confidence Level ◽  
Certainty Factor ◽  
Forward Chaining ◽  
Calculation Results ◽  
Manual Calculation

The purpose of this research is to create an expert system application to diagnose diseases in the rambutan plant that can be accessed anytime and anywhere so that the handling of the disease can be done appropriately. The Forward Chaining and Definity Factor methods are used because they are very suitable for expert systems that diagnose something that is uncertain so that the manual calculation results from the symptom data and the existing expert values result in a 98.91% confidence level percentage, and solutions are given to treat disease-stricken plants. The implementation uses Android Studio so that the application can run dynamically on various devices so that farmers can immediately find out what is happening with the conditions of their rambutan plants directly.Keywords:Rambutan Plant, Expert System, Android, Forward Chaining, Certainty Factor.

scholarly journals Media Konsultasi Penyakit Kulit Pada Balita Menggunakan Metode Certainty Factor

2020 ◽  
Vol 3 (1) ◽  
pp. 10-17
Author(s):  
Sudi Utari ◽  
Uky Yudatama ◽  
Bambang Pujiarto
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Human Body ◽  
Skin Diseases ◽  
The Body ◽  
The Sun ◽  
Test Results ◽  
Certainty Factor ◽  
Factor Method ◽  
The One

The skin, which is the largest part  of the human body, is the body's first defense against bacterial and virus attacks. When the skin is exposed to the sun, dry weather, or bacteria, the reaction will spread to other parts of the body, and can even result in death if it is too late to be handled especially if the sufferers are children who are very vulnerable to disease. In this study an expert system was implemented to diagnose skin diseases in infants using the certainty factor method. certainty factor method is very suitable for expert systems that diagnose something that is uncertain. This system makes a diagnosis based on the symptoms felt by the user and then calculates certainty factors based on existing symptoms. Based on the test results by making comparisons between manual calculations and the one carried out by the system it is known that 90.22% of the diagnosis results get the same results so that the system is said to be suitable for use.  

scholarly journals Expert System for Chili Plants Disease Detection using Certainty Factor Method

2019 ◽  
Vol 9 (1) ◽  
pp. 1145-1151
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Programming Language ◽  
Disease Detection ◽  
Certainty Factor ◽  
Web Based ◽  
Factor Method ◽  
Delone And Mclean ◽  
The Creation ◽  
Design And Manufacture

This paper describes the creation of an expert system that is used to diagnose diseases in chili plants using a web-based certainty factor method. This expert system is made based on the weight of symptoms by experts so that users can find out the disease suffered by chili plants based on symptoms that arise. The symptom weight was calculated using the certainty factor method. This method is used to accommodate uncertainties that are often expressed by experts when detecting a disease. The design and manufacture of this expert system are done using the PHP programming language, MySQL database, CSS and the CodeIgniter framework. The results of the analysis between expert and expert systems have 87.09% compatibility level, and based on the calculation of the feasibility of the system with the Delone and McLean model shows that 77.58% of respondents agree Pakarcabaiku.com is a successful system for detecting chili disease.

scholarly journals Sistem Pakar dalam Menganalisis Penyakit Kelenjar Getah Bening Menggunakan Metode Certainty Factor

2021 ◽  
pp. 269-274
Author(s):  
Sri Layli Fajri ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Lymph Node ◽  
Expert System ◽  
Lymph Nodes ◽  
System Analysis ◽  
The Body ◽  
Certainty Factor ◽  
Accuracy Rate ◽  
Factor Method ◽  
Analysis Process ◽  
Node Disease

In general, a person is difficult do dermine whether a lump or swelling of the lymph nodes in the body, is just a normal lump or whether it has become cancer. If the lumph does not go away whitin a few days, the patient is required to immediately consult a doctor to get detailed information about the disease and how to treat it. Lymph nodes scattered in the human body are round and are part of the lymphatic system that plays a role in fighting viruses that enter the body. The cause of these enlarged lymph nodes can be due to the type of food consumed, congenital disease in the patient’s body (comorbid), infection to lymph node cancer (lymphoma). For this reason, an Expert System is needed by applying the Certainty Factor method in order to assist the public in analyzing lymph node disease by answering several questions regarding the symptoms experienced. This system is implementad using the PHP programming language and MySQL database. The result of this study show that the Certainty Factor method can work well in the Expert System analysis process. From the result of system trials with several patient data, the disease accuracy rate in the patient named S is 63% and the disease accuracy rate in the patient named MR is 68%. Besides being useful for an expert, this Expert System can help patients to find out the type of disease they are suffering from, the accuracy of disease, the method of treatment and a guide for making decisions.

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