Certainty Factor Method Research Articles

Diagnosis Of Respiratory Tract Infections In Toddlers With Expert System Using Variable-Centered Intelligent Rule System And Certainty Factor Method

Expert system can help the experts in diagnose the Respiratory TractInfection For Toddlers. This research have a purpose to build anexpert system for Android with Kotlin language using Variable-Centered Intelligent Rule System and Certainty Factor method, alsoget the accuracy of it. System’s input is a yes or no answer from Yes-No Question with user. This research use 164 patient data of toddlersat UPTD Kenten Laut Banyuasin Health Center and variables which issymptoms that occurs in toddlers such as cough, cold, hard to breathe,fever, and the results of a physical examination conducted by theexpert. Based on test result, the system has 95,52% accuracy whendiagnose ISPA case, and 100% accuracy when diagnose Pneumoniacase. So, it can be concluded that Variable-Centered Intelligent RuleSystem and Certainty Factor method can be used to diagnoserespiratory infections in toddlers.

Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia

Uatzau basin in northwestern Ethiopia is one of the most landslide-prone regions, which characterized by frequent high landslide occurrences causing damages in farmlands, non-cultivated lands, properties, and loss of life. Preparing a Landslide susceptibility mapping is imperative to manage the landslide hazard and reduce damages of properties and loss of lives. GIS-based frequency ratio, information value, and certainty factor methods were applied. The landslide inventory map was prepared from detailed fieldwork and Google Earth imagery interpretation. Thus, 514 landslides were mapped, and out of which 359 (70%) of landslides were randomly selected keeping their spatial distribution to build landslide susceptibility models, while the remaining 155 (30%) of the landslides were used to model validation. In this study, six factors, including lithology, land use/cover, distance to stream, slope gradient, slope aspect, and slope curvature were evaluated. The effects of the landslide factor of slope instability were determined by comparing with landslide inventory raster using the GIS environment. The landslide susceptibility maps of the Uatzau area were categorized into very low, low, moderate, high and very high susceptibility classes. The landslide susceptibility maps of the three models validated by the ROC curve. The results for the area under the curve (AUC) are 88.83% for the frequency ratio model, 87.03% for certainty factor, and 84.83% of information value models, which are indicating very good accuracy in the identification of landslide susceptibility zones of a region. From these resulted maps, it is possible to recommend, the statistical methods (Frequency Ratio, Information Value, and Certainty Factor Methods) are adequate to landslide susceptibility mapping. The landslide susceptibility maps can be used for regional land use planning and landslide hazard mitigation purposes.

Landslide hazard assessment of rainfall-induced landslide based on the CF-SINMAP model: a case study from Wuling Mountain in Hunan Province, China

The traditional Stability INdex MAPping (SINMAP) model does not perform detailed divisions of study areas and neglects differences caused by the asymmetrical spatial distribution of geotechnical parameters; thus, the accuracy of the evaluation results is insufficient. In this study, the evaluation results of the SINMAP model were improved based on a combination with the certainty factor (CF) model, and the proposed method is referred to as the CF-SINMAP model. The Wuling Mountain area in Cili County of Hunan Province (China) was selected to verify the CF-SINMAP model. First, eight geological environmental factors in the region were analyzed by the CF method, including the slope, distance from fault, slope direction, distance from water, rock and soil type, elevation, distance from road and vegetation coverage. The rock and soil type, vegetation coverage and human engineering activities were determined as the key factors underlying landslide hazards. Then, the study area was divided into six regions based on the key factors, and the physical and mechanical parameters of each region were refined by the natural environment, formation lithology and human activities. Finally, the CF-SINMAP model was used to calculate and analyze the landslide hazard assessment results under different rainfall conditions. The results show that the CF-SINMAP model is more sensitive to rainfall compared with the traditional method and the unstable areas are mainly distributed along river valleys, reservoir banks and areas with continual human engineering activities. The area under the receiver operating characteristic (ROC) curve values was 0.75 and 0.61 for the CF-SINMAP and SINMAP models, respectively. Compared with the traditional SINMAP model, the CF-SINMAP model produces more reliable results. The rainfall threshold that induced the landslide disaster in Cili County, Hunan Province, was 90 mm/d. In summary, the CF-SINMAP model provides new ideas for the prediction of regional rainfall-induced landslides.

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

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%.

Certainty Factor for Online Game Addiction Scale Diagnosis — A Case Study of Informatics Student, University of Khairun

Online game addiction is the behavior of someone who wants to always play online games that lasts a long time and allows the individual concerned to not be able to control it so that it can have a negative impact that can have a negative impact on health and mental if too frequently play it. The aim of this study is to diagnose the online game addiction scale to students using the certainty factor algorithm. The level of online game addiction will be divided into three levels, namely: mild, moderate and severe addiction diagnoses. The calculation process starts from determining the weight value of each symptom and then determining the weight value of the user then calculating the weight value of each symptom with the user’s weight value using the certainty factor method so as to produce how large the percentage level of online game addiction. The results showed that from a number of processed data the diagnostic results were obtained 13% of students with mild addiction, 37% of students with moderate addiction, 50% of students with severe addiction.

Application of Expert System with Smartphone-based Certainty Factor Method for Hypertension Risk Detection

Hypertension is a factor health problem with a high prevalence in Indonesia. The total amount of hypertension nationwide is 34.11%. There are only 1/2 were diagnosed, and the remaining 1/2 are undiagnosed. Certainty factor was needed to prove the certain or not of a fact in a metric form, and it commonly was used in expert systems. This method was perfect for diagnosing something uncertain. This research aimed to build a smartphone-based hypertension risk detection system. This system was built by MPX5500DP pressure sensor components that served for blood pressure measurement, Bluetooth module HC-05 as microcontroller data transmission, Arduino Uno as sensor data processing, and Smartphone as hypertension risk detection interface and database access. Measuring blood pressure on the user's right or left arm was used to test the system. Then the data was sent to the smartphone to be classified and processed by using the certainty factor method implanted in the android smartphone to detect the risk of hypertension and then followed by the selection of symptoms and risk factors of hypertension according to previous experience. The results showed that the success rate of the system in detecting the risk of hypertension was 100%, the mean error of the systolic value of the right arm was 2.092%, and the average error of the diastolic value of the right arm was 2.977%, while the average error of the systolic value of the left arm. 1.944% and the mean error of the left arm diastolic value was 2.800%.

Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Identifikasi Penyakit Panleukopenia pada Kucing

Feline Panleukopenia is a disorder caused by inflammation of Feline Parvovirus. This viral inflammation can trigger inflammation of the digestive system in cats and can also attack the cat's bone marrow, and the total white blood cells in the cat's body will decrease. At this time, many people do not know how to accurately identify the disease Feline Panleukopenia in cats and as a result of that cats who suffer from it experience illness and even death. This study aims to determine the level of accuracy in identifying Panleukopenia in cats. There are several types of symptoms that refer to Feline Panleukopenia. Furthermore, the data is processed manually with the Certainty Factor method and continued by using a website-based expert system software. The processing stages are rule solving, determining the weight value of each symptom and calculating the Certainty Factor value with the rule formula. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 5 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of feline panleukopenia. Expert testing systems have been able to specifically identify Feline Panleukopenia. Through the Certainty Factor method, the level of accuracy that can be obtained is quite accurate and can help veterinarians improve their accuracy to identify Feline Panleukopenia in cats.

Sistem Pakar Menggunakan Metode Certainty Factor Dalam Akurasi Identifikasi Penyakit Panleukopenia Pada Kucing

Feline Panleukopenia is a disorder caused by inflammation of Feline Parvovirus. This viral inflammation can trigger inflammation of the digestive system in cats and can also attack the cat's bone marrow, and the total white blood cells in the cat's body will decrease. At this time, many people do not know how to accurately identify the disease Feline Panleukopenia in cats and as a result of that cats who suffer from it experience illness and even death. This study aims to determine the level of accuracy in identifying Panleukopenia in cats. There are several types of symptoms that refer to Feline Panleukopenia. Furthermore, the data is processed manually with the Certainty Factor method and continued by using a website-based expert system software. The processing stages are rule solving, determining the weight value of each symptom and calculating the Certainty Factor value with the rule formula. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 5 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of feline panleukopenia. Expert testing systems have been able to specifically identify Feline Panleukopenia. Through the Certainty Factor method, the level of accuracy that can be obtained is quite accurate and can help veterinarians improve their accuracy to identify Feline Panleukopenia in cats.

Sistem Pakar Menggunakan Metode Certainty Factor untuk Estetika Kulit Wanita dalam Menjaga Kesehatan

The skin is an important organ located on the outside of the human body that needs to be kept healthy. Good skin health will certainly increase self-confidence, especially for women. Lack of information about diseases and treatment solutions and the small number of professional estheticians means that women end up not consulting when skin problems arise. If left untreated, skin problems will be more serious. The purpose of this study was to identify the accuracy of skin problems in women so that a solution in caring for the skin was obtained. The data processed in this study are the results of an interview from an aesthetic doctor about skin problems in women and the solutions and symptoms experienced by patients. Then the data obtained manually were processed using the Certainty Factor method and tested with a website-based system. The processing stage of this method is the compilation of symptoms into rules, giving weight values ​​for each symptom and calculating based on the Certainty Factor rule formula. The results of testing this method were 13 data on aesthetic skin diseases identified from 15 trial data. So that the level of accuracy is 86.67%. The results of this test have been able to identify well. The Certainty Factor method used can identify quite specifically and can be recommended to skin aesthetic doctors in increasing accuracy for identifying skin problems in women.

Perbandingan Naïve bayes dan Certainty factor pada Sistem Pakar Untuk Mendiagnosa Dini Penyakit Glaukoma

Glaucoma is an eye disease that causes the second largest blindness after cataracts, this disease can cause decreased vision and can even be fatal, namely permanent blindness if it is not realized and treated immediately. Lack of information and education to the public to always maintain eye health is the basis for the purpose of making this expert system which aims to provide early diagnosis to people who are indicated to have glaucoma based on the symptoms or characteristics previously felt. The Naïve bayes method is a method that uses statistics and probability in predicting a person's chance of suffering from glaucoma based on the symptoms previously felt. It is made based on a website with PHP as the programming language and uses MySQL for the database. As for the comparison method used is the Certainty factor, which is a method that functions to determine a certainty value based on the calculation of the predetermined CF value by applying manual calculations. In the Naïve bayes method, the application can group symptom data and types of disease and can diagnose based on previous training data, while for the Certainty factor method based on the calculation of the value of the expert and the CF value that has been inputted by the user, it can produce a percentage of the diagnosis of the disease glaucoma in 96%.Keywords:Certainty factor, Expert System, Glaucoma, MySQL, Naïve bayes, PHP.

Sistem Pakar Diagnosa Kerusakan VGA dengan Metode Certainty Factor dan Algoritma K-Nearest Neighbor (K-NN)

VGA (Video Graphics Array) is a Video adapter which is very useful for improving the performance and quality of the visual process on a computer, but sometimes there is often a malfunction that cannot be identified the type of damage. The problem is the lack of media to identify the damage that occurs during visual processing. Therefore, the authors created an expert system that can diagnose the type of damage to VGA using the Certainty Factor method as a calculation, using UML modeling as the work process flow of the system on the website, and also equipped with the KNN (K-Nearest Neighbor) algorithm as machine learning. so that it can build an expert system with the PHP programming language MySQL database. The method used in testing is the black box method in testing the system used. The results that can be concluded from this study are; 1) The diagnostic system for detecting damage to the VGA uses the K-Nearest Neighbor Algorithm as machine learning and the Certainty Factor Method as a calculation medium in determining the distance from the type of damage and has suggestions for further actions to deal with and prevent the damage from occurring and also has other possible damage things that are similar to the damage suffered can be accessed quickly and easily to understand, in making scientific research carried out sequentially to facilitate the process, and 2) In addition to diagnosing, there are several additional menus that can be accessed such as the Prediction menu which functions to displays the max and min limits of the temperature of a product, Product Info which functions as a quality product recommendation, and a description that contains a post of details of the damage that can be studied and is expected to help users find solutions to their problems.Keywords:Expert System, PHP, Certainty Factors, Machine learning, K-NN.

Development of Expert System for Cataract Self Screening in Android Mobile Platform Based in Pamekasan City: Case Study

Cataract is one of the biggest causes of blindness in Indonesia. More than 3,0% of the population in Indonesia is becoming blind and still increasing. There are so many people who still don’t realize that they are suffering from cataracts because of lack of access to a nearby eye clinic or hospital with an opthamologist. In this research, an application in mobile platform android has been developed to help people to screen by themselves and give a recommendation of opthamologists near them for checkup. An expert had made a decision about weighted in the symptoms and diagnosis in the system using the certainty factor method. The results show the kind of cataract and its weight that was suffered by users and give recommendations to nearby eye clinics

Application for Calculating Psychological Pressure in the DASS (Depression, Anxiety, and Stress Scale) Scale Using the Certainty Factor Method

Psychological stresses such as depression, anxiety, and stress often experienced by students can affect academic performance, physical health, and psychosocial well-being. The purpose of this research is to build a facility in the form of a website-based application for students in particular and the general public in order to know the level of psychological pressure they are experiencing. The psychological scale used is the DASS-21 (Depression, Anxiety, and Stress Scale) and the calculation uses the Certainty Factor method. In carrying out this research, there are three main stages that are carried out, namely; The first stage, looking for literature studies related to research. Second stage, conducting interviews with experts to get a certainty value on the scale that the researcher uses. Then, build an expert system using prototype development methods and web-based applications. The third stage, implementation was carried out by getting Computer Technology student respondents. This research is a new domain for the NSC Surabaya Polytechnic which will implement an expert system by utilizing the Certainty Factor method in analyzing student stress levels through intelligent applications that will be implemented in the form of a website, with the calculation of Certainty Factors, the application can produce evidence or analysis that can be used. in changing the learning system.

Modeling of Landslide susceptibility in a part of Abay Basin, northwestern Ethiopia

AbstractThe study area in northwestern Ethiopia is one of the most landslide-prone regions, which is characterized by frequent high landslide occurrences. To predict future landslide occurrence, preparing a landslide susceptibility mapping is imperative to manage the landslide hazard and reduce damages of properties and loss of lives. Geographic information system (GIS)-based frequency ratio (FR), information value (IV), certainty factor (CF), and logistic regression (LR) methods were applied. The landslide inventory map is prepared from historical records and Google Earth imagery interpretation. Thus, 717 landslides were mapped, of which 502 (70%) landslides were used to build landslide susceptibility models, and the remaining 215 (30%) landslides were used to model validation. Eleven factors such as lithology, land use/cover, distance to drainage, distance to lineament, normalized difference vegetation index, drainage density, rainfall, soil type, slope, aspect, and curvature were evaluated and their relationship with landslide occurrence was analyzed using the GIS tool. Then, landslide susceptibility maps of the study area are categorized into very low, low, moderate, high, and very high susceptibility classes. The four models were validated by the area under the curve (AUC) and landslide density. The results for the AUC are 93.9% for the CF model, which is better than 93.2% using IV, 92.7% using the FR model, and 87.9% using the LR model. Moreover, the statistical significance test between the models was performed using LR analysis by SPSS software. The result showed that the LR and CF models have higher statistical significance than the FR and IV methods. Although all statistical models indicated higher prediction accuracy, based on their statistical significance analysis result (Table 5), the LR model is relatively better followed by the CF model for regional land use planning, landslide hazard mitigation, and prevention purposes.

Implementasi Sistem Pakar menggunakan Metode Certainty factor Untuk Mendiagnosa Penyakit Herpes Zoster

Herpes Zoster is a skin disease that is very difficult to treat and everyone can certainly experience it, the characteristics of this disease are characterized by unilateral vesicles in groups with pain characterized by radicular around the dermatome. This study aims to establish a Web-based Certainty factor method as a tool to diagnose skin diseases. With this application, it doesn’t need long time to find out what type of herpes zoster is suffering. To use this application is that the patient answers the questions which are provided by the system, then the system will process all the patient answers using the certainty factor method, after that, the system will produce output as the results of the diagnosis of the type of shingles. The system built can help patients to know the type of disease that is being suffered by the patients and in accordance with expert analysis of skin diseases.Keywords:Certainty factor, Herpes zoster, web.

Application of the borderline-SMOTE method in susceptibility assessments of debris flows in Pinggu District, Beijing, China

According to information provided by the residents of Pinggu District, Beijing, 79 gullies were investigated. Based on the results of field investigations, 65 gullies were classified as debris flow gullies, and 14 were classified as non-debris flow gullies. By using ArcGIS software, the area and the quantity information of various factors affecting the occurrence of debris flows were obtained. The frequency ratio method was used to obtain the combinations of factors conducive to the debris flow occurrences in the study area. The susceptibility of debris flows in Pinggu District was evaluated by the information value method, certainty factor method, and logistic regression (LR) method. When using the LR method, the number of positive and negative samples should be balanced; therefore, the borderline-SMOTE method was used to generate samples belonging to the minority class. By comparing the results obtained by the three methods, it was found that the results obtained by the LR method are best. This result indicates that for disaster susceptibility assessments, the borderline-SMOTE method can be used to synthesize samples. The susceptibility evaluation results show that debris flows are more likely to occur in the southeast part of Pinggu District.

Expert System For Detection Glaucoma Disease Using Certainty Factor Method

Glaucoma is an eye disease that attacks nerves of human eye and it’s often not realized by sufferer until further damage to the eye nerve occurs. Glaucoma is second most common cause of permanent blindness according to Indonesian Ministry of Health. Permanent blindness caused by glaucoma can be avoided by early detection of disease and appropriate regular treatment. Early detection needed in an effort to prevent glaucoma can be done using an expert system. Expert system is an artificial intelligence program that can make reasoning and thinking like an expert in a particular field. Expert systems with certainty factor methods can describe level of certainty of expert expressions such as possible, most likely, and almost certain. Thus everyone can use an expert system to do glaucoma examination. In this research, diagnosis results will be obtained in the form of a percentage of a person’s CF value for glaucoma which is calculated using the certainty factor method based on the CF value of the symptoms entered by the user. Based on results of tests conducted, there are 8 out of 9 case data that are in accordance with the results of expert system diagnosis using certainty factor method that has been built. In other words, expert system has 90% accuracy in diagnosing glaucoma.

Application of the Certainty Factor and Forward Chaining Methods to a Goat Disease Expert System

Goats are livestock that is financially very attractive to rural Indonesian. Efforts to solve problems related to goat farming are necessary. One of them is maintaining the health of the cattle by knowing how to cope with disease-stricken goats. Goat productivity will decrease if the treatment of the disease is sub-optimal. Goat diseases are very diverse, ranging from mild to severe. Breeders themselves can traditionally treat several diseases without the involvement of veterinarians or experts. However, a larger number of diseases need treatment with the help of experts. Expert systems are a potential solution to help farmers. It will automatically suggest decisions or conclusions in solving a problem. This study observes an expert system built using the Certainty Factor combined with Forward-Chaining. By combining the two methods, the information generated may discover the type of disease and suggest its management effectively with a high degree of certainty. The system can expectedly become a reference for goat breeders to consult about their goat livestock diseases. The knowledge base of the system uses 21 types of symptoms, eight types of diseases, and their solutions. The user does not need to input the belief value and the disbelief value that is usually input in the expert system. By involving the admin as a knowledge base processor, the correctness of the conveyed information maintains.

Analisa Certainty Factor Dalam Mendiagnosa Kerusakan Alat Pemancar Radio 87.6 Dass FM Lubuk Pakam

An FM transmitter or FM transmitter is a source of radio vibrations emitted by a device called an oscillator or oscillator. While the oscillator is a device that can produce high frequencies. The scope of this research is an expert system that is built only to discuss the symptoms and damage to radio transmitters and solutions to fix them. The resulting output is radio transmitter malfunction information and solutions to repair it. The programming language used in solving this problem is PHP by using the mysql database. The method used in solving the damage to the radio transmitter is the certainty factor method.

Aplikasi Sistem Pakar Dengan Metode Forward Chaining Dan Certainty Factor Untuk Mendeteksi Penyakit Ayam

The development of computer technology now is really fast. The computer is not only used as a tool to complete the work of humans but can also run applications designed to access information quickly. Application of expert system application is moved to a computer expert knowledge. So the computer could also resolve the problem as usual is done by specialists. Expert system has been widely developed in various fields, including the field of animal husbandry. Chicken breeders usually get the chicken disease information from the livestock extension officers. But sometimes often constrained because the number of extension officers of the cattle that are not evenly distributed in each area. Therefore, the breeder can access information about diseases of chicken with the help of the method of Forward Chaining and Certainty Factor into the making of the application. The resulting application is an expert system for detecting diseases of chickens that could be used to assist farmers in obtaining information about the disease of chickens and handling solutions.