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Typhoid fever is a significant health issue caused by the Salmonella Typhi bacteria, leading to symptoms such as fever, abdominal pain, diarrhea, muscle pain, and serious complications if not treated promptly. A common challenge faced by society is limited access to medical professionals, especially in remote areas, and delays in recognizing symptoms. To address this problem, this study designs and implements a web-based expert system using the Certainty Factor (CF) method, which helps diagnose typhoid fever quickly and accurately. The Certainty Factor method is used to calculate the certainty level of the symptoms experienced by the patient, providing a diagnosis result in the form of early-stage typhoid, mild typhoid, or severe typhoid. The system was developed using PHP programming language and MySQL database, and tested at RSUD Djoelham Binjai City. The research data was obtained from patients at RSUD Djoelham Binjai with a case study on patient number 22. The processing of symptoms through Certainty Factor calculation showed that the patient is most likely to have severe typhoid with a certainty value of 0.9443 or 94.43%. This result proves that the Certainty Factor method can be used to assist in providing an accurate early diagnosis of typhoid fever with a high degree of accuracy.

Groundnut plants must be well maintained so that they can be food crops that have economic value and high fat and protein content. Many farmers still plant with the old pattern so that peanut plants are less fertile because they are affected by pests and other diseases. So with an expert system to diagnose peanut plants can help farmers or the general public in knowing the solution if experiencing problems or symptoms of this peanut plant. The application of the WP (weighted product) method can help the application become structured. From the results of the study, the expert system for diagnosing peanut plants can help many people for use as fundamental insights.

An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, combining knowledge and rules obtained from experts to diagnose problems, provide advice, or make complex decisions, especially in notebook damage, so this requires the design of an expert system application for diagnosing notebook damage based on a website for users who support the diagnosis process using the certainty factor method, in terms of explaining the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated using the formula in CF, the final result is the creation of a website-based notebook damage diagnosis expert system.

Hypertension is a common disease in society and can lead to serious complications if not properly managed. This study aims to design a web-based expert system to assist in diagnosing hypertension using the Certainty Factor and Dempster Shafer methods. The Certainty Factor method is used to measure the confidence level of reported symptoms, while the Dempster Shafer method combines information from various sources to generate more accurate decisions. The system is designed with a user-friendly interface to facilitate access for medical personnel and patients. The research results show that the Certainty Factor method achieved an accuracy 97,9%, while the Dempster Shafer method reache 96,4%. The accuracy difference of 1,4% indicates that the Certainty Factor method is more effective in handling the uncertainty of hypertension symptoms than the Dempster Shafer method.

An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, combining knowledge and rules obtained from experts to diagnose problems, provide advice, or make complex decisions, especially in dental diseases, so this requires the design of an expert system application for website-based dental disease diagnosis with a UML model for users who support the diagnostic process using the certainty factor method, in terms of the explanation of the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated with the formula in CF, the final result is the creation of a website-based dental disease diagnosis expert system.

An expert system is a computer program designed to imitate the decision-making ability of an expert in a particular field, especially in printer damage, so this requires an expert system application to diagnose printer damage to users who support it by obtaining diagnostic results using the certainty factor method, in terms of the explanation of the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated using the formula on the certainty factor, the final result is the creation of an expert system for diagnosing printer damage using the website-based certainty factor method.

The development of computer technology helps many aspects of life. One aspect of life that takes advantage of technological developments is the health sector, in order to solve problems including brain tumors. Brain Tumor Disease is the growth of abnormal cells in or around the brain in an unnatural and uncontrolled manner. Patients with brain tumors continue to increase every year, because the initial symptoms are often underestimated. Therefore created a software that can help diagnose brain tumors using the certainty factor method

Expert systems are one type of computer technology that is being used by a used in the medical field to assist physicians in patient examinations is expert systems.The goal of this is to improve patient care both now and in the future.system with expertise  is an application that replicates how an expert would reason to solve a particular problem or acts similarly to an expert due to its understanding of a knowledge base that has to be processed and its ability to solve problems. An expert system's diagnosis of epilepsy leads to the creation of a system that can offer individuals with the condition a consultation service for the purpose of diagnosing the condition and providing information on treatment options. This is demonstrated by the development of numerous technologies that facilitate the work of numerous parties. One of them is computer-related and uses Expert System Science to assist in the diagnosis of epilepsy. The Certainty Factor approach is employed in this study. Thirteen symptoms and three different forms of epilepsy—general, partial, and secondary—were used in this investigation. The study's findings indicate that, based on the chosen symptoms, the most accurate diagnosis is Partial Primary, Partial Secondary, with a confidence level of 74%, and the most accurate diagnosis is Generalized Epilepsy, with a confidence level of 99%.    

The objective of Waikabubak Regional Hospital's information system deployment is to streamline the administrative procedure. Information system performance must be measured or audited to ascertain its maturity in order to give information technology a positive role and to ensure that it operates in line with the hospital's planning and business objectives. Information system audits conducted with the COBIT 4.1 Framework are highly beneficial to management, auditors, and users alike. Determining the information system's maturity level at Waikabubak Regional Hospital is the goal of this study.  The ability to offer suggestions that can be used as raw material for future information system improvements is another goal of this research. The study's findings display the system maturity level score.  From a total of 20 sudomains, the information gathered at Waikabubak Regional Hospital is 3 or at level Defined Process; only 6 of these indicated a score of level 2 maturity level (Repeatable but Intuitive), which is provided as a recommendation.. Keywords: Expert System, Epilepsy, Certainty Factor    

Tomatoes are plants that were first discovered in South America, closely related to eggplant, potatoes and peppers. Tomato is a fruit that has an attractive red color and is rich in vitamins such as vitamin C. So it is not wrong if tomatoes are very useful for maintaining the body's immune system. Each 100 grams of tomatoes contains 20 calories of calories, 1 gram of protein, 0.3 grams of fat, 4.2 grams of carbohydrates, 5 milligrams of calcium, carotene (vitamin A) 1500 SI, thiamin (vitamin B) 60 micrograms, ascorbic acid (vitamin C). ) 40 milligrams, phosphorus 27 milligrams, iron 0.5 milligrams, potassium 360 milligrams. Tomatoes are also vegetables or ingredients for cooking that are sought after by people to meet their daily needs. This makes the supply of tomatoes from farmers is always in shortage. The lack of supply of tomatoes in the market is caused by a decrease in tomato production or yields. This decrease in production was caused by several obstacles, one of the obstacles that caused crop failure was due to disease. Disease attacks on tomato plants can occur from planting to harvest. Diseases that often attack penicillin plants are sptoria leaf spot, anthracnose fruit bud, fusarium and verticium wilt, brown spot and late blight. Therefore, to handle this, of course, sufficient knowledge is needed to deal with and deal with pests and diseases in tomato plants appropriately. To overcome this, it is necessary to build a system that can diagnose diseases in tomato plants. So that farmers are able to overcome and deal with pests and diseases on tomato plants appropriately. Researchers have done a lot of research by building an expert system to diagnose a disease. With the results of research, an expert system is designed to assist farmers and agricultural extension workers in detecting diseases in soybean and rice plants. From the results of tests that have been carried out using an expert system, 14 different cases in the field are then cross-checked with the results of expert analysis and have a suitability of 93%.

Obsessive-Compulsive Disorder (OCD) is a psychiatric disorder characterized by uncontrollable obsessive thoughts and compulsive behaviors. The disorder triggers anxiety in sufferers that often drives them to avoid situations or places that can trigger obsessions, such as shaking hands or using public restrooms. Proper treatment is necessary to prevent further impact on the quality of life of OCD sufferers. However, early diagnosis is often constrained by limited time and access to medical experts. To overcome this, an expert system based on the Certainty Factor method was developed. This system mimics the thought process of a medical expert in diagnosing OCD using symptoms selected by the user. Certainty Factor is used to calculate the certainty level of each diagnosis based on the inputted symptoms. From the analysis, the system is able to provide diagnoses with high accuracy, even reaching 100% for some OCD cases. These results show that expert systems can be an effective tool in detecting OCD early, thus accelerating the process of proper handling and treatment

Vulvodynia is a chronic pain condition affecting the vulva that significantly impacts women’s quality of life. Accurate and early diagnosis poses a challenge due to the often-overlapping symptoms with other conditions and the lack of definitive diagnostic tests. This paper proposes the use of expert system methods as a diagnostic tool for vulvodynia in women. The expert system, integrating medical knowledge with inference algorithms, is designed to analyze symptoms, medical history, and test results to provide accurate diagnoses and treatment recommendations. The study involves the development and evaluation of a computer-based expert system prototype that uses clinical data and medical decision-making to enhance the accuracy of vulvodynia diagnosis. Preliminary results indicate that the expert system can improve diagnostic rates and reduce the time required for identifying this condition, offering a potentially valuable tool for medical professionals in clinical practice.  

Nasal hypertrophy is a swelling that occurs in the nasal concha. This condition is caused because the inferior concha has a larger anatomical size when compared to the other concha structures. The process of diagnosing nasal hypertrophy often requires high clinical skills and experience. RSU Putri Bidadari is one of the hospitals that treats Nasal Hypertrophy disease in patients. Nose hypertrophy disease has several symptoms that are felt which are usually caused by several factors such as exposure to certain allergens, chronic sinus infections, or a family history of similar nasal problems, so several diagnostic tests are needed that can confirm the diagnosis, such as nasal endoscopy to see directly the condition inside the nose, medical imaging such as CT scan or MRI to evaluate the structure of the nose in more detail, or allergy tests to identify the causative allergen. From the above problems, patients really need a system that becomes a recommendation in helping provide information about nasal hypertrophy disease that can diagnose early and take further action to prevent nasal hypertrophy disease. By using the certainty factor method, information from the steps above can be systematically analyzed to determine the level of confidence in the diagnosis of nasal hypertrophy. These factors can be assessed based on severity, presence of typical symptoms, correlation with risk factors, and results of physical examination and diagnostic tests. Based on the results of the CF calculation, the highest value is in the type of nasal hypertrophy disease with the type of Septal Deviation disease having a value of 1 or 100%, in the type of Rhinitis disease having a value of 94.24% and in the type of sinusitis disease having a value of 85.60%. From the results obtained, the system identifies that the patient has nasal hypertrophy with Septal Deviation type by 100%.  

: Oyster mushrooms are one of the popular horticultural products in the community, with a significant increase in demand from year to year. However, farmers often face difficulties in identifying and preventing diseases that attack oyster mushroom plants, which have an impact on production stability. To overcome this problem, this study aims to design an expert system that can diagnose diseases in white oyster mushrooms using the Dempster Shafer Method. This system is designed to provide accurate diagnostic information and solutions to deal with diseases in oyster mushrooms, so as to improve the quality and quantity of production. This study also strengthens previous studies using the Certainty Factor method, with an emphasis on the use of expert knowledge to overcome disease problems in oyster mushroom cultivation. The case study was conducted at Omah Jamur Tiram Stabat, where the results of the implementation are expected to increase the effectiveness and efficiency of oyster mushroom cultivation in the area.

The rapid development of information technology affects the way people access information, including in the health sector. Prostate cancer, as one of the most significant types of cancer in men, is often detected late due to lack of information and limited costs. To overcome this problem, a system is needed that is able to diagnose prostate cancer quickly, precisely, and accurately. This study aims to develop a web-based expert system using the Certainty Factor (CF) method to diagnose prostate cancer based on the symptoms that appear. The CF method was chosen because of its ability to determine the level of confidence in the facts or rules used in the diagnosis. This study uses data on symptoms and types of prostate cancer. The results of the study can help the public in recognizing prostate cancer symptoms early, with a high level of accuracy in diagnosis. This study is expected to make it easier for patients to make an early diagnosis and accelerate the treatment of prostate cancer.

Dermatitis is an inflammatory skin disease that is accompanied by itchy skin. It occurs in infants, and gets better in adolescence, but some cases can persist for a long time or even develop the disease in adulthood. In general, if you have this skin disease, you should see a skin specialist for a consultation. However, skin specialists are not always at the hospital, making it difficult for patients to arrange appointments to meet or consult. Therefore, the hospital needs to have an additional system that can help facilitate the medical team to detect the type of dermatitis disease based on symptoms (blistering skin, redness of the skin, scaly and dry skin, dark skin, blistering skin, cracked skin that is present in the disease, atopic dermatitis, contact dermatitis, seberoic dermatitis, nummular dermatitis, and intertriginous dermatitis and get handling and understanding of dermatitis disease using the certainty factor method. From the analysis carried out, the results of the diagnosis of the selected symptoms are obtained, the most accurate diagnosis is Atopic Dermatitis 98% with the treatment given, namely Corticosteroids and Antihistamines to patients.  

Chikungunya is a disease caused by the Chikungunya virus (CHIKV) transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Some of the symptoms are sudden fever, chills, pain in the joints, muscle pain in the neck, shoulders and limbs, rash. Treatment of sufferers is aimed at complaints and symptoms that arise and the drugs given are generally only to relieve existing symptoms, such as giving Antipyretic drugs to relieve fever, Antiemetic drugs to relieve nausea / vomiting, or Analgetics to relieve joint pain only, from these problems many people also do not understand the handling of chikungunya disease, therefore it is necessary to have a system that can collect information to collect information and conduct counseling activities on the treatment of Chikungunya disease to the general public and especially to the elderly to provide knowledge about Chikungunya disease using the Certainty Factor method. The purpose of this research is to provide information and knowledge to the public about Chikungunya Disease Treatment and the Elderly know the medicine for Chikungunya Disease treatment. From the results of applying the certainty factor method to diagnose chikungunya disease, it can be obtained that the diagnosis result is acute chikungunya disease with a confidence level of 95.19%.

An expert system is a computer program that imitates the decision-making abilities of an expert in a particular field. This system uses a knowledge base and logical rules to analyze problems and provide solutions or recommendations, helping users who do not have in-depth knowledge of the topic, then along with the development of website-based information technology which can make it easier to identify student interests, talents, especially grades 4 and 5 carried out by the teacher, this includes the potential of each individual student according to their category so as to provide an accurate solution. The aim of this research is that an application of an expert system for identification of talent interests for users is needed which supports the teacher analysis process using certainty factors, based on certainty factors which have a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, then calculated using the certainty factor formula, the output research on the creation of an expert system for identifying student talent interests using a website-based certainty factor method which produces diagnostic results for talent interest categories.    

An expert system is a device designed with the thought processes of one or more experts in specific or complex fields of knowledge. This system is built on instructional elements that identify and analyze data to address unstructured problems or conduct mathematical analyses of particular issues. With the advancement of web-based information technology, computer damage detection becomes easier for users. Therefore, a web-based expert system application using the certainty factor method is needed to detect computer damage. The certainty factor method works based on symptoms and diagnoses weighted by experts and user input. These weights are then calculated using the certainty factor formula to produce a confidence level in the given diagnosis. The end result is the creation of an expert system application capable of detecting computer damage for users using the web-based certainty factor method. This application not only enhances efficiency in detecting damage but also facilitates maintenance processes by providing a history of damage detection, thereby reducing the time required for repairs. Thus, this application offers an effective and efficient solution for computer damage detection. Additionally, this application can be continually developed and adapted to user needs, making it a highly useful tool in computer maintenance across various environments.

Kucing adalah hewan peliharaan populer yang sering kali rentan terhadap berbagai penyakit. Ketidakmampuan pemilik untuk mendiagnosa penyakit kucing secara tepat waktu sering kali mengharuskan konsultasi dengan dokter hewan yang sebagian besar hanya tersedia di perkotaan. Penelitian ini bertujuan mengembangkan sistem pakar berbasis web menggunakan metode Forward Chaining dan Certainty Factor untuk membantu mendiagnosa penyakit pada kucing. Metodologi pengembangan sistem ini mencakup tahap persiapan, prototyping, dan penyelesaian. Pada tahap persiapan, masalah dirumuskan dan wawancara dengan dokter hewan dilakukan untuk membangun knowledge base. Tahap prototyping melibatkan pembuatan mesin inferensi dan knowledge base, sementara tahap penyelesaian meliputi implementasi sistem ke dalam antarmuka pengguna berbasis web menggunakan PHP dan framework Laravel. Hasil uji sistem menunjukkan konsistensi tinggi dengan hasil diagnosa manual menggunakan Excel. Sebagai contoh, diagnosa penyakit Virus Panleukopenia memiliki nilai certainty factor sebesar 94,62% pada aplikasi, sementara perhitungan manual menunjukkan 95,21%, dengan perbedaan hanya 0,41%. Hal ini menunjukkan bahwa sistem pakar yang dikembangkan mampu memberikan diagnosa yang cepat dan akurat. Kesimpulannya, sistem pakar berbasis web ini dapat diandalkan untuk mendiagnosa penyakit kucing dan membantu dokter hewan serta pemilik kucing melakukan diagnosa awal dengan lebih efisien.