Certainty Factor Method Research Articles

IMPLEMENTATION OF INFERENCE ENGINE WITH CERTAINTY FACTOR ON POTENTIAL DIAGNOSIS OF BRAIN TUMOR DISEASE

An expert system is a system that has the ability of experts or experts who master a particular field to assist in solving problems. Certainty factor (CF) is one of the methods in an expert system that can define the level of certainty based on facts to show the level of confidence of the expert. This study aims to apply a certainty factor (CF) algorithm to solve the problem of diagnosing potential human brain tumors. Because the symptoms that are felt are not necessarily brain tumors, it is necessary to analyze whether the person has the potential to have a brain tumor or not, even if the potential level is. Brain tumor disease is one of several types of dangerous conditions. This disease is caused by the abnormal growth of cells around the brain. This research produces an application that can diagnose potential brain tumor diseases based on symptom input selected by the user. Then the expert system can display the diagnosis results in percentages and solutions from the results of the diagnosis. The study results indicate that the CF method can solve the problem of uncertainty by giving a degree of confidence from an expert and system user. The accuracy test results resulted in an accuracy value reaching 95%. These results indicate that the system can function and can diagnose potential brain tumor diseases properly

Penerapan Metode Certainty Factor Dalam Diagnosis Gangguan Depresi

Globalization can cause several problems and pressures of mind for both individuals and groups. Various kinds of problems can certainly lead to psychological disorders, one of which is depression. Indonesia itself is one of the countries with a high number of people with depressive disorders. Depressive disorder itself can have many consequences ranging from lack of enthusiasm to even death. Facing these serious problems, the government should be able to address the mental disorder that is currently happening. However, the reality is still far from this. Inadequate infrastructure, equality problems for each region, and shortages of experts are the main problems at this time. The expert system is considered to be a solution in solving these problems. Web-based expert systems can replace the role of experts in the process of initial diagnosis of depressive disorders, patients can also access them easily. The calculation method implemented is the Certainty Factor method. This method is considered suitable in the diagnosis of depression. The implementation of the CF method in the diagnosis of depression can provide a confidence level of up to 94.9%. The expert system is expected to be able to eliminate human errors, speed up the diagnostic process, make it easier for health workers, and provide standards for related parties in handling mental disorders

Expert System to Diagnose Bonsai Plant Pests with Certainty Factor Method

Bonsai ornamental plants are dwarf plants which are generally planted in shallow pots. The main element in bonsai is harmony between pots and plants, in addition to harmony between pots and plants there are also other elements such as trunk size, tree height, root distribution, twigs, and leaf size as well as diseases and pests that attack the bonsai plants need to be considered. The difficulty of the community in conducting consultations and the unavailability of funds and time, so that the community has never conducted consultations about diseases and pests that attack their bonsai plants to experts or plant extension workers from the relevant agencies. Therefore, it is necessary to take action to anticipate the increasing number of bonsai farmers who do not consult on diseases and pests of bonsai plants. This is due to the delay in the diagnosis of the disease. The unavailability of experts or plant extension workers who are close, the community does not have time to conduct consultations and requires money. An expert system is a computer-based system that uses knowledge, facts, and techniques and reasoning in solving problems that can usually only be solved by an expert in the field. The Certainty Factor method is efficient enough to be used in diagnosing the diseases and pests of the bonsai plant. This system can provide early diagnosis of diseases and pests on the bonsai plant based on the symptoms and intensity of the symptoms that are visible from the outside. Users only need to enter the Web to take the first step in solving bonsai plant diseases and pests and choose the symptoms of the disease they are experiencing without having to ask an expert directly. This system is made web-based with PHP programming language and MySQL database.

Identifikasi Faktor Kegagalan Hasil Produksi Busa dengan Sistem Pakar Metode Dempster Shafer dan Certainty Factor

Foam is a derivative product made from PPG (Propylene Glycol) or Polyether Polyol which is then mixed with additives and catalysts. So it will produce foam that is used in the springbed and mattress industry. The foam is produced first by using a mixer machine. After the mixer, dispensing will be carried out (pouring the material into the mold) then the foam will be blown off and the foam production process is complete. Failure to produce foam often results in losses in terms of raw materials, costs, and time. To avoid the failure of the same foam production, a research was carried out by designing an expert system application that aims to be able to identify the factors causing the failure of foam production and to reduce the risk of failure of foam production. The data needed in this study were obtained from PT Bungo Permai Lestari. The data is then processed using the Dempster Shafer method and the Certainty Factor method. The results of this study are to provide output in the form of certainty values from failure of foam production, factors causing failure of foam production, as well as solutions to failure of foam production obtained through consultation using the Dempster Shafer method and the Certainty Factor method by selecting symptoms that match the results. foam production. So this research can help PT Bungo Permai Lestari to find out the causes and solutions to the failure of foam production and can reduce the risk of failure during foam production.

Sistem Pakar Kombinasi Metode Certainty Factor dan Dempster Shafer

An expert system is a technique of artificial intelligence that uses certainty techniques to solve problems. There are several techniques that can be used to solve the problem of uncertainty, including the certainty factor method and the mathematical theory of Dempster Shafer. Both methods and techniques can be applied to solve expert system problems. However, each method has advantages and disadvantages in determining the diagnosis. In the expert system, there are 2 values ​​used for the diagnosis process, including the expert value taken from the expert hypothesis and the user value or evidence which is the value obtained based on the facts of an event. Dempster Shafer theory can only use the evidence value in determining the density value, while the certainty factor method can use evidence and hypothesis values. Thus, the combination made to overcome the weakness of one method by using the advantages of the other method is expected to produce a better certainty value.

Expert System to Diagnose Bonsai Plant Pests With Certainty Factor Method

Bonsai ornamental plants are dwarf plants which are generally planted in shallow pots. The main element in bonsai is harmony between pots and plants, in addition to harmony between pots and plants there are also other elements such as trunk size, tree height, root distribution, twigs, and leaf size as well as diseases and pests that attack the bonsai plants need to be considered. The difficulty of the community in conducting consultations and the unavailability of funds and time, so that the community has never conducted consultations about diseases and pests that attack their bonsai plants to experts or plant extension workers from the relevant agencies. Therefore, it is necessary to take action to anticipate the increasing number of bonsai farmers who do not consult on diseases and pests of bonsai plants. This is due to the delay in the diagnosis of the disease. The unavailability of experts or plant extension workers who are close, the community does not have time to conduct consultations and requires money. An expert system is a computer-based system that uses knowledge, facts, and techniques and reasoning in solving problems that can usually only be solved by an expert in the field. The Certainty Factor method is efficient enough to be used in diagnosing the diseases and pests of the bonsai plant. This system can provide early diagnosis of diseases and pests on the bonsai plant based on the symptoms and intensity of the symptoms that are visible from the outside. Users only need to enter the Web to take the first step in solving bonsai plant diseases and pests and choose the symptoms of the disease they are experiencing without having to ask an expert directly. This system is made web-based with PHP programming language and MySQL database.

Penerapan Forward Chaining dan Certainty Factor Pada Sistem Pendeteksi Penyakit Hewan Qurban Berbasis Android

Qurbani worship is a worship of the slaughter of livestock carried out on the feast of Eid al-Adha. In Indonesia the dominant livestock used for qurban worship is goats and cows, qurban animals that are allowed to be slaughtered also have conditions ranging from age and most importantly their health. This research is done so that goats and cows that will be slaughtered for qurban worship are free from existing diseases. Some of the problems in the system that will be built is the lack of understanding of the sellers of animals qurban about the diseases suffered by goats and cows from the symptoms experienced by these animals. This study used the method of forward chaining and certaity factor in solving the problems that exist in goat and cow animals, to produce a conclusion in detecting diseases in these animals based on existing symptoms. The process of designing the application of disease detection expert systems in goat and cow animals uses the java programming language and uses a text editor android studio. The authors also tested the comparison of the combination method between forward chaining and certainty factor with the forward chaining and naïve bayes methods that received the highest percentage value results, namely in the forward chaing and certainty factor methods with a value of 9.553%. in scab disease suffered by goat animals and a value of 9.509%in bloating disease suffered by cow animals. Getting the final result on the calculation of detection of goat disease by 91,264% with indicated suffering from scab disease and also in cow animals by 90,432% indicated to suffer from bloating disease, both the final results of the calculation of the type of disease suffered by goats and cows respectively seen from the symptoms that have been inputted by the user.

Diagnosa Penyakit Tulang Belakang Menggunakan Metode Forward Chaining dan Certainty Factor

In the field of medicine, especially orthopedics, there are several types of spinal diseases including scoliosis, lordosis, kyphosis, and spondylosis. Therefore, an expert system is needed to diagnose spinal diseases. Based on this problem, we performed an exponential comparison of the two hybrid methods. With the final value of the combined forward chaining & naive bayes method of 8.89, and 9.40 the highest final value of the combined forward chaining method and certainty factor. So that in this research, forward chaining and certainty factor methods are used which are designed based on a website, using Sublime Text 3 programming tools and PHP and MySQL as databases. From the results of application testing and manual calculations with 30 sample data, it was concluded that 7 users or about 23% entered the level of confidence in the possibility of developing spinal disease and 23 users or 77% of the total testing stated at the level of confidence in the probability of developing spinal disease with a value of the highest confidence of 88.5% in spondylosis disease.

Sistem Pakar Deteksi Dini Penyakit Preeklamsia pada Ibu Hamil Menggunakan Metode Certainty Factor

Preeclampsia is a disease in pregnant women characterized by high blood pressure and positive urine protein. The disease has a high risk of maternal and fetal death, so there is a need for early detection of mothers at risk of preeclampsia. Early online detection of preeclampsia is the best solution during the Covid-19 pandemic by analyzing the influencing factors. The purpose of this study is to build an expert system for early detection of preeclampsia in pregnant women using the Certainty Factor method and the waterfall system development model in order to provide the possibility of pregnant women suffering from preeclampsia. Testing the accuracy of 30 medical record data for pregnant women resulted in a system accuracy level of 90%, while usability testing resulted in a user satisfaction level of 55 with the System Usability Testing (SUS) score criteria being "Poor", therefore improvements are needed on expert system in the future.

Sistem Pakar Mendiagnosa Penyakit Tropik Infeksi Dengan Menggunakan Metode Certainty Factor (CF)

The impact of computer technology has played a major role in changing aspects of human life, especially in the health sector where in the midst of an epidemic that hit a system that is able to reduce the impact of the crowd is needed. One of them is a system for diagnosing disease, and the disease to be studied is a type of infectious disease and a disease that is increasing in the midst of an epidemic, namely infectious tropical diseases or diseases that develop in a tropical climate. The purpose of this study is to build a web-based expert system application that is able to diagnose infectious tropical diseases using the certainty factor (CF) method, and development using the waterfall model. Tests are carried out with blackbox tests and validity tests, on blackbox tests the system runs as expected and on the validity test the system is declared valid to be used. In the user test, the calculation obtained using the CF method is 97.65% certainty level. The research concludes that the system is able to provide a confidence value and can diagnose the type of infectious tropical disease based on the symptoms selected by the user. Because the system still has limitations, it is hoped that the system will be developed using other methods so that it is more useful for users.

Sistem Pakar Diagnosa Gangguan Pencernaan Pada Manusia Menggunakan Metode Certainty Factor

Along with advances in science and technology, especially in the field of medicine, more sophisticated medical equipment will be produced in fighting disease or making early detection of disease so that treatment can be faster. One of them is digestive disorders in humans. The purpose of this study is to build an expert system application that is able to diagnose digestive disorders in humans based on the symptoms experienced by implementing the Certainty Factor method. The development of an expert system uses the waterfall model, which consists of the stages of analysis, formulating problems, collecting data, and testing. The implementation of the Certainty Factor method in this expert system is used to generate a level of confidence in the diagnosis of the disease. The expert system was tested through 3 stages of testing, namely blackbox test, validity test and user test. In the blackbox test, the system functions run as expected. In the validity test, the system is declared valid for use. In the user test, respondents gave the criteria of "Eligible". From the results of the study, it can be concluded that the system is able to provide a trust value and can diagnose digestive disorders based on the symptoms entered by the user. Because the system is still limited, it is hoped that there will be system development with other methods so that it is more useful for users

Sistem Pakar Mendiagnosa Penyakit Ayam Kampung Menggunakan Metode Certainty Factor

Animal husbandry is the activity of breeding and raising livestock to obtain the benefits and results of these activities. Activities in the field of animal husbandry can be divided into two groups, namely livestock farming of large animals such as cows, buffaloes and horses, while the second group is farming of small animals such as chickens, ducks, birds and others. Village chicken farming activities have existed since ancient times. Village chickens start from the first generation, namely from the descendants of the red jungle fowl (Gallus gallus). Raising free-range chickens is not easy because there are many things that must be considered and must have problems, therefore an expert system is needed to assist farmers in diagnosing and knowing the type of disease and symptoms experienced by the free-range chicken using a computer system automatically. This expert system uses the Certainty Factor method which aims to measure the level of certainty of facts or rules to describe an expert's belief in the problem at hand. This study shows how the process of calculating the Certainty Factor method in diagnosing free-range chicken disease with the initial combination rule to the last combination rule based on the selected symptoms, it can be concluded that the highest weight value is D01 Avian Influenza with a weight value of 0.99 x 100% = 99%

Sistem Pakar Diagnosa Penyakit Tetelo Menggunakan Metode Certainty Factor

In today's technological era, computers are not only used as a tool to complete human work but can also run applications designed to access information quickly. Expert systems are one part of artificial intelligence. An Expert Systems application is an application that transfers expert knowledge to a computer. That way the computer can also solve problems as is usually done by experts. Expert systems have been widely developed in various fields, including the field of animal husbandry. Detection of tetelo disease can use an expert system application. One of them is to detect Tetelo disease. Therefore, breeders can access information about Tetelo disease that is diagnosed with the help of an expert system that uses the Certainty Factor method. The Certainty Factor method serves to determine the degree of certainty of the diagnosis result.

Mental Health Helper: Intelligent Mobile Apps in the Pandemic Era

Every human being faces various episodes of events that can cause changes in mental health conditions, including this coronavirus pandemic disease. The ups and downs of the psychological turmoil dynamics resulted, and also traumatic feelings can occur continuously or for a certain period. It can cause an adverse response for those who experience it and even cause anxiety or mental disorders. The implementation of restrictions on community activities during these pandemic circumstances makes people who want to check their mental health condition difficult to meet the experts or professionals such as psychologists. Therefore, the application that can detect these anxiety disorders as early as possible to minimize unwanted effects was developed. In the making of the application, an expert system is used to determine the results of the diagnosis. The expert system requires knowledge that is produced from experts, especially in the psychology field. The data that has been obtained will be processed and then yield the results determined from the classification of anxiety types using several methods in Artificial Intelligence. Several tests were carried out 50 times using Certainty Factor methods to obtain an accuracy rate of 96%. It has similar accuracy compared to the Naïve Bayes method. This application called Mental Health Helper has a validity and reliability test to prove that this application is valid and reliable. It has better performance than previous researches, which still only has two classes of diseases.

Comparison of Certainty Factor (CF) and Case Based Reasoning (CBR) to Diagnose Infertility in Women

Infertility has now become a terrible and serious problem for women. Limited information about infertility suffered by women makes it difficult for them to predict the disease they are suffering from. Therefore we need an expert system that can predict infertility in women. The methods used in this research are Certainty Factor (CF) and Case Based Reasoning (CBR) methods. Certainty Factor (CF) is one of the techniques used to overcome uncertainty in decision making. Case Based Reasoning (CBR) is a problem solving method by remembering similar events that happened in the past and then using that knowledge or information to solve new problems. Based on the test results using 25 test data, the accuracy of the expert system for diagnosing infertility in women using the Certainty Factor (CF) method is 92%, while the curation of the expert system for diagnosing infertility in women using the Case Based Reasoning (CBR) method is 76%.

Sistem Pakar Diagnosis Penyakit Lupus Berbasis Mobile Application Android dengan Metode Certainty Factor (CF)

The objectives of this research are; 1) Creating Android software or applications using the Certainty Factor method, and 2) Early diagnosis of a person's indications using the Certainty Factor (CF) method. The research methodology uses interviews, collects information obtained, the next stage is used with the Certainty Method used to calculate the probability value of MD, MB and CF, researchers to display the diagnosis of Lupus, testing techniques using Acceptance Testing techniques. The results of the study have succeeded in making an application using the JAVA programming language assisted by the Android SDK Platform. The results of the disease obtained a confidence value indication of Dry Eyes, Shortness of Breath due to Lung Inflammation, Continuous Chest Pain for Lupus is 0.968815.

Sistem Pendeteksi Gejala Stunting pada Anak dengan Metode Certainty factor Berbasis Website

The purpose of this study is to design and develop a stunting symptom detection system in children using the Website-based certainty factor method which aims to create a stunting symptom detection system in children from an early age and help parents in maintaining nutrition in their children, indirectly said to be computerized to detect stunting means that when applied, it makes it easier for parents to monitor nutrition quickly and precisely. This study uses a system development method where the model used is Waterfall. The results of this study are in the form of an application that provides several symptoms of stunting in children then the user can conduct consultations to determine the calculation of the results of stunting symptoms correctly. The use of this certainty factor method is implemented in an expert system that is used to look for symptoms caused by stunting and in solving the case, the certainty factor obtains an accuracy of 80%.

Sistem Pakar Diagnosa Kerusakan Hardware Komputer Menggunakan Metode Forward Chaining dan Certainty Factor Berbasis Website

Computers have become a huge requirement to support human performance. Computers also often experience Hardware damage such as processors, VGA, motherboards, memory, mouse, keyboards, hard disks, optical drives, monitors. Until now, many computer users still do not have sufficient knowledge of the initial diagnosis of computer Hardware damage which causes a lot of computer users to pay a lot of money to find out and repair the damage that occurs to Computer Hardware. In this Expert System application research development, the authors use a combination of two inference methods, namely the Forward Chaining method and the Certainty Factor Method. The programming tools used in the development of this Expert System application is using the Sublime Text 3 application while the database uses MySQL with PHP as the programming language. The purpose of this Expert System application is made to assist computer users in making an initial diagnosis of a damaged computer Hardware along with the causes and solutions to overcome the damage.

Sistem Pakar Bimbingan Konseling Menerapkan Pola 17 Plus dengan Metode Forward chaining dan Certainty factor Berbasis Web

A formal education institution is an institution that specifically aims to educate the younger generation before entering the world of work or lectures. With the existence of a school, it can provide smoothness in achieving optimal development for the younger generation, one of which is the existence of counseling services for the 17 plus pattern. This study aims to make it easier for teachers to approach students to identify students' interests and talents. Implementation of a website-based counseling application, from the problems that have been described, a system is needed that can facilitate teachers in handling student counseling. This expert system uses two methods, namely the forward chaining method to handle the facts of each question given by students and the certainty factor method used by the teacher to determine the treatment taken in consulting student interests and talents. System testing using the certainty factor method produces values from each field including personality field 49.67%, career field 67.94%, learning field 76.67%, and social field 71.67%.

APLIKASI SISTEM PAKAR DALAM MENDETEKSI KERUSAKAN AC RUMAH BERBASIS ANDROID DENGAN MENGIMPLEMENTASIKAN METODE CERTAINTY FACTOR

The current global warming season, Air Conditioning or AC, is a tool that is very useful for the community, because AC can cool a room. With its ability to cool a room, this air conditioner is often used continuously by the public, which makes it quickly damaged. When this AC device is damaged, people are confused and restless in repairing it. Moreover, coupled with the current Covid-19 pandemic, people are increasingly afraid to use the services of an AC technician, for fear of contracting the corona virus. This problem can be overcome by building a system where the system can help the community in diagnosing AC damage. The system is called an expert system to diagnose damage to home air conditioners using the Android-based certainty factor method. The result of this research is that with the application of this expert system, it can help the community in diagnosing AC damage and the level of accuracy in diagnosing AC damage using the certainty factor method is 80%.