Application Of Expert System Research Articles

Aplikasi Sistem Pakar Kopi Mendeteksi Hama Kopi Di Desa Telagah Kecamatan Sei Bingai Kabupaten Langkat

The use of coffee expert applications can help farmers detect pest attacks based on symptoms of attacks on coffee plants. This study aims to determine the application of the coffee expert system to coffee farmers, determine the diversity of insect species and pest status on coffee plants in Telagah Village, Sei Bingai District, Langkat Regency, North Sumatra. Insect identification was carried out by the Plant Pest Laboratory, Faculty of Agriculture, University of Sumatra Utara which was carried out from July to August 2023. This study used purposive sampling method with yellow sticky trap. The results showed insects caught as many as 10 orders, 21 families, 25 genera as many as 4743 individuals. The results of the analysis of Coffee Experts detected Hypothenemus hampei pest attack = 6.80%. Diversity Index (H') = 1.91, evenness index (E) = 0.59 and species richness index (R) = 8,46. The use of coffee expert applications can help farmers detect pests appropriately.

Penerapan Metode Case-Based Reasoning pada Website SORTING (Sorong Atasi Stunting) Sebagai Implementasi Smart City (Studi Kasus: Distrik Sorong Timur)

Stunting is one of the issues designated as a national priority issue at this time. Determining this priority issue is to accelerate the level of achievement of national development goals. East Sorong District, Sorong City, Southwest Papua Province is one of the focus location with a high prevalence rate. This study aims to develop an information technology called SORTING (Sorong Atasi Stunting) using the case-based reasoning method. This research produces a system that can be accessed from anywhere and at any time, which can be used by residents, especially mothers, to consult regarding their baby's growth problems. SORTING was developed using the expertise of nutritionists who usually deal with stunting problems. SORTING resulted in several conclusions that the application expert system can diagnose stunting by using the case-based reasoning method as an engineering approach to the knowledge base; The application of the SORTING expert system can provide an overview of stunting including the results of the percentage of diagnoses, factors and recommendations for solutions that must be taken; The application of the SORTING expert system can be used as a second alternative to consult with experts in diagnosing stunting. And it can also be an alarm to continue consulting with experts directly; The application of the SORTING expert system can increase knowledge about stunting. The researchers hope that SORTING can assist the government in the National Action Plan for Stunting Management which emphasizes reducing stunting rates and can help the community recognize stunting diseases early and prevent them.

Web-Based Expert System Application for Early Diagnosis of HIV/AIDS Using the Naive Bayes Method

AIDS is a progressive decrease in the immune system so that opportunistic infections can appear and end in death, therefore the author created an early diagnosis system for HIV/AIDS using the website-based Naïve Bayes algorithm. Naïve Bayes is a simple probability classification that can calculate all possibilities by combining a number of combinations and frequencies of a value from the database obtained.the results of the research obtainedThe naïve Bayes algorithm can be implemented for early diagnosis of HIV/AIDS by means that the existing HIV/AIDS symptom data is adjusted to the patient's symptom data processed using the naïve Bayes algorithm and then it is concluded what the symptoms are and What is the solution.

Pengembangan Aplikasi Sistem Pakar Preferensi ‘Bahasa Cinta’ Manusia Berbasis Web

The purpose of this research is to produce a web-based expert system application to identify a person's love language using the nave Bayes classifier method. This expert system application to identify a person's love language is intended for people who have not realized how important it is to know which love language is relevant to them. This expert system application to identify a person's love language provides guidance in the form of questions about the type of love language. The answers to the questions asked will lead to the final decision on the results of the expert system diagnosis. Sources of expert system application knowledge base obtained from books and the internet. In making the application using the extreme programming software development method. Extreme programming consists of four stages, namely: planning, design, coding, and testing. The result of this research is the application of an expert system of love language identification that works on a web base.

Designing an Expert System for Evaluating Student Stress Levels: A Novel Instrument Using Backward and Forward Chaining Methods

Academic stress is a problem that students often experience, especially when completing final studies such as writing a thesis. This research aims to develop an instrument for measuring students' academic stress levels based on an expert system using forward chaining and backward chaining methods. The research method used is research and development (RD) with a Borg and Gall design which includes 10 steps. These steps include: (1) Research and information collecting, (2) Planning, (3) Developing a preliminary form of the product, (4) Preliminary field testing, (5) Main product revision, (6) Main field testing, (7) Operational product revision, (8) Operational field testing, (9) Final product revision, and (10) Dissemination and implementation. By following these steps, the research ensures a systematic and thorough development process, leading to a reliable instrument for measuring academic stress. The data collection instrument was the Guttman model academic stress scale (SSA) with 48 valid and reliable items (rxy = 0.785). Data was obtained from 319 IAIN Batusangkar student respondents which were processed descriptively. The results showed that 34.8% of respondents experienced high levels of academic stress, 32.6% moderate, and 32.6% low. Furthermore, this research develops a web-based expert system application to detect students' academic stress levels by using forward chaining, which starts from data to reach a conclusion, and backward chaining, which starts from a goal to verify it with available data. These methods ensure accurate stress level assessments. Through this technological approach, the research provides a comprehensive solution for managing and reducing student academic stress effectively and efficiently, with findings showing that the expert system significantly improves early detection and personalized stress management strategies for students.

Pemodelan Sistem Pakar Identifikasi Tingkat Stres Karyawan dengan Metode Certainty Factor

Expert systems work by collecting knowledge from experts in the form of rules or knowledge bases, then using an inference engine to analyze situations and produce decisions or suggestions. Apart from that, it is often used in the fields of medicine, engineering, finance, etc., related to this, especially the process of identifying the level of stress experienced by employees in the company so that they can find out more, therefore an expert system application design is needed for identification using the method. certainty factor, based on 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, calculated using the formula in CF, the final result is the creation of an expert system application for identifying employee stress levels based on a website.

EXPERT SYSTEM DIAGNOSES VARICOCHEL DISEASE USING MAMDANI'S FUZZY LOGIC ALGORITHM METHOD

Varicoceles form when valves in the veins that run along the spermatic cord (the structure that suspends the testicles in the scrotum) prevent blood from flowing properly. Most varicocele cases occur during puberty, from the age of 15 to 25 years. If there are symptoms that are not prolonged, treatment is not necessary. However, if a varicocele causes pain, shrinkage of the testicles, impaired fertility, or swelling, surgery will be performed. Symptoms of this disease are similar to hemorrhoids and bladder stones, so it takes an expert. In the research conducted on the Expert System Application for Diagnosing Hyperthyroid Disease with the Mamdani Fuzzy Logic Inference Method, it can be concluded that the expert system can store expert knowledge from experts in solving problems diagnosing hyperthyroid disease while Mamdani fuzzy inference is used for knowledge processing in order to obtain a more accurate diagnosis conclusion. definitely with accuracy . Making the application is expected to make it easier for people to get information without having to wait for the presence of a doctor/expert for varicocele disease, and is expected to reduce or even solve existing problems.

Pendeteksian Kerusakan Komputer Editing Sinetron Pada Sistem Pakar Dengan Metode Certainty Factor

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.

Cat Disease Diagnosis Expert System Using Web-Based Forward Chaining Method

Currently, technological developments are growing rapidly. It can be seen from that most human activities require technology to meet daily needs. Technology has now fulfilled human needs that can be done by themselves. One of them is an expert system. Cats are one of the animals that are popular among people. Because it is so popular, the number of cat enthusiasts in Indonesia has become very large, and will continue to grow. However, this is not balanced by the knowledge of the keepers and the availability of sufficient veterinarians. This research develops an expert system application to diagnose diseases in cats. This expert system has 7 knowledge bases about diseases in cats and 30 symptoms, using the forward chaining inference method. The expert system was built and designed using the PHP programming language. The expert system provides output in the form of disease diagnosis results in cats based on the symptoms input by the user. The expert system developed is useful for helping the public obtain information about cat diseases and their symptoms easily and quickly

Enhancing Supply Chain Safety and Security: A Novel AI-Assisted Supplier Selection Method

The "Make or Buy” decision and the supplier selection are critical steps for the efficient operation of companies' supply chains. Safety and security are paramount considerations, especially in industries like logistics, where supply chains are vulnerable to external threats and disruptions. In this scientific article, we present a novel Artificial Intelligence (AI)-assisted supplier selection method that significantly enhances the safety and security of suppliers. During our research project, we have created an expert system and a corresponding knowledge base with the relevant rules to support supply chain decision-makers in selecting logistics service providers for warehousing services. The foundation of the AI-assisted supplier selection method is advanced data analytics and the application of expert systems, enabling companies to evaluate potential suppliers in detail from a safety and security perspective. The applied expert systems can identify potential risks and make predictions about supplier performance in the future. In the turbulent environment of the global supply chain, selecting long-term partners like warehousing services providers is critical for the success of the organization. A wrong supplier selection can hardly be reversed in warehousing services, as the cost of change is usually high. The article demonstrates the practical application of the expert system-assisted supplier selection method in a real-world supply chain environment and thoroughly analyzes the achieved results and advantages. The results show that the expert system-assisted method not only increases supplier safety and security but also contributes to improving the efficiency and sustainability of the supply chain. This article provides valuable guidance and solutions for companies looking to enhance their supplier selection using expert system technologies, thereby increasing the safety and security of their supply chains.

Rancang Bangun Aplikasi Sistem Pakar Diagnosis Penyakit Jantung: Studi Kasus pada Klinik Siaga Menggunakan Metode Case-Based Reasoning (CBR) Berbasis Web

In the era of modernization, technological advancements are developing rapidly and play an essential role in various aspects of life, including healthcare. Technology enables people to easily access information in fields such as business, education, and health. In the medical field, computer-based expert systems assist professionals in diagnosing diseases and solving specific problems. This study focuses on developing an expert system application for diagnosing heart diseases using the Case-Based Reasoning (CBR) method, implemented as a web-based system with PHP and MySQL. The heart, a vital organ responsible for pumping blood, is slightly larger than a fist (around 200–425 grams). According to Dr. Helmanu Kurniadi and Ulfa Nurrahmani, S.Kep., smoking is identified as one of the contributing factors to heart disease. The developed application consists of five primary elements, with several menus such as the homepage, user data, disease information, disease list, and login page. Based on black box testing, the application has been thoroughly tested to ensure it functions correctly and is free from coding errors. Additionally, acceptance testing was conducted eight times, resulting in a 100% accuracy rate, aligning with the intended design. Thus, the application is ready to be deployed and is expected to assist both the public and healthcare professionals in diagnosing heart diseases effectively.

A Modification Depth First Search (DFS) Algorithm for Troubleshoot Rotating Equipment Diagnosis

Rotating Equipment has a role in the industrial production process. There are times when the equipment that is being operated has trouble. Operators have difficulty dealing with problems of rotating equipment due to limited knowledge. To solve this problem we must have an expert with knowledge and experience. Based on this, the problem is building an expert system application to diagnose troubleshoot on rotating equipment which aims to transfer the knowledge that an expert has into the computer so that operator can find out what problems occur. This paper use Depht First Search (DFS) method, namely inward tracing techniques and Forward Chaining, namely the inference method that uses reasoning where to test a hypothesis starts from a fact. This system is equipped with an expert menu for knowledge management, so that experts can add, edit, and delete knowledge. The results showed that DFS and Forward Chaining are very suitable for diagnosing troubleshooting on Rotating Equipment. Based on the reasoning of the experts in their field and adjusted to the symptoms experienced by equipment so that the type of damage is found. It can also assist operators in diagnosing troubleshoot on Rotating Equipment so that operators can take preventive action to prevent further damage to the equipment.

SISTEM PAKAR DIAGNOSA PENYAKIT SAPI

In the livestock industry, the health of cattle is crucial because diseases can lead to a decrease in production, animal deaths, and economic losses. The high incidence of these diseases is due to ignorance and lack of knowledge about them. Therefore, an expert system was developed to diagnose diseases in cattle. The method used in creating this expert system is forward chaining using the PHP programming language and MySQL database. The result of this research is an expert system application for diagnosing diseases in cattle using forward chaining method, which can be accessed by the public, especially farmers and traders, to identify diseases in cattle, with the hope of improving the efficiency of diagnosis. This system can speed up the disease detection process, minimize human errors, and enable faster and more accurate decision-making by combining artificial intelligence with web technology.

Sistem Pakar Diagnosis Hama dan Penyakit pada Tanaman Padi menggunakan Metode Certainty Factor

This study aims to develop a web-based expert system application using the Certainty Factor method to diagnose pests and diseases in rice plants. The system is designed to assist farmers, particularly in the Barus Subdistrict, Central Tapanuli Regency, in identifying and addressing pest and disease issues that frequently affect rice crops. The development process includes analysis, design, implementation, and testing of the application. Testing results indicate that the application successfully identifies pests and diseases with an accuracy rate of 95%, based on comparisons with manual diagnoses provided by experts. Additionally, the application is user-friendly, allowing farmers to easily select symptoms present in their rice plants and receive accurate diagnoses and appropriate solutions. The user-friendly interface further enhances the ease of use. This study differs from previous research in terms of the types of pests, symptoms, solutions, and the research location.

Sistem Pakar Diagnosa Hama Penyakit Tanaman Kentang Dengan Metode Forward Chaining

Potatoes (Solanum tuberosum L.) are a priority vegetable crop due to their high domestic trade value and export potential. Potatoes are used for various purposes, both as a vegetable and as a carbohydrate substitute. In addition to being used as a vegetable, potatoes are also utilized as raw materials in the food industry, such as chips, potato flour, and potato starch. Due to the relatively low temperature requirement (20-22°C) for tuber formation, potato cultivation areas in Indonesia are generally located in mountainous regions. One of the potato commodity centers is in the city of Batu, particularly in the Bumiaji District. According to vegetable crop potential data from the Batu City extension program in 2022, the area planted with potatoes is 485.2 hectares with a production potential of 968 tons. Since potato plants are more susceptible to pests and diseases, substandard maintenance can lead to low harvest yields, poor sales, and even crop failure. This issue has led to the development of an application for diagnosing potato pests. The expert system uses forward chaining methods and is web-based. The expert system processes facts answered by users of the potato application, diagnoses the symptoms present, and generates diagnostic results in the form of solutions for the diagnosed potato plant diseases or pests. With the availability of an expert system application for diagnosing potato plant diseases and pests, the limitation of expert manpower is no longer a hindrance for potato farmers. Recommendations and information regarding potato diseases and pests can be obtained online without the need to consult a specialist.

Sistem Pakar Diagnosa Penyakit Akibat Virus Pada Manusia Menggunakan Metode Teorema Bayes

An expert system is a computerized application that aims to imitate the reasoning process of an expert in solving certain problems and making decisions or conclusions because their knowledge is stored in a knowledge base to process problem solving. The basis of an expert system is how an expert's knowledge is transferred to a computer and used to make decisions and draw conclusions based on that knowledge. Many expert system applications have emerged in the medical field. By answering questions on an application similar to consulting a doctor, this expert system allows ordinary people to detect diseases based on the symptoms they experience. In this way, lay people can also identify diseases and treatment solutions early, which allows for rapid treatment and disease prevention. This system aims to provide support to medical personnel in carrying out initial diagnoses, increasing diagnostic accuracy, and assisting in making medical decisions more quickly and efficiently. The use of the Bayes Theorem method allows the system to handle uncertainty and variations in the symptoms experienced by patients, so as to provide more accurate results.

APPLICATION OF MATHEMATICAL MODELS IN THE DIAGNOSIS OF DISEASES OF INTERNAL ORGANS

The application of diagnostic expert systems in medical technology signifies a notable progression, as they provide a computerized framework for decision-support, assisting healthcare practitioners in the process of disease diagnosis. These systems facilitate the integration of patient data, encompassing symptoms and medical history, with a knowledge base in order to produce a comprehensive compilation of potential diagnoses. Through the utilization of knowledge-based methodologies, they enhance these potentialities in order to ascertain the most probable diagnosis. The present study examines expert systems, investigating their historical development, architectural structure, and the approaches utilized for knowledge representation. There is a significant emphasis placed on the advancement and implementation of these systems within the medical industry of Kazakhstan. This paper provides a comprehensive analysis of the benefits and drawbacks associated with diagnostic expert systems, emphasizing their potential to bring about significant advancements in medical fields. The study places significant emphasis on the necessity of developing and conducting thorough testing of these systems in order to improve the precision and effectiveness of medical diagnostics. The statement recognizes the importance of continuous research in order to enhance the design and implementation of these systems in various healthcare settings. This research makes a notable addition by examining optimization theory in the field of medical diagnosis. This study presents novel approaches for effectively addressing the intricacies and uncertainties associated with the diagnosis of complicated disorders. The work presents methodology for navigating the complex field of medical diagnostics by utilizing mathematical modeling and optimization approaches, specifically the gradient projection method. The utilization of diverse ways to tackle qualitative ambiguities in this approach signifies a significant progression inside the domain of diagnostic expert systems.

Application of mivar expert systems in the fight against telephone fraud

Application of mivar expert systems in the fight against telephone fraud

Penerapan Metode Dempster Shafer Sistem Pakar Pada Penyakit Tuberkolosis

The Dempster-Shafer (DS) method is a method in trust theory that is used to overcome uncertainty in decision making. An expert system that utilizes the Dempster-Shafer method can be used to diagnose tuberculosis (TB). Application of the Dempster-Shafer method in an expert system for TB requires a good understanding of the medical domain and the ability to correctly combine evidence from multiple sources. In addition, collaboration with medical experts in developing this system will increase the accuracy and usefulness of the expert system. At the Wonokromo Community Health Center, the use of websites to diagnose tuberculosis is still lacking, therefore the aim of using this website is to help the community know more about tuberculosis. In the design process, this system uses a user interface, and is equipped with HTML, CSS, Boostrap, and Java Script. The result of this research is a website-based expert system application using the website-based Dempster Shafer method, and is able to overcome the problems that exist at the Wonokromo Community Health Center. The black box testing results show that the module configuration functions well and meets user needs.

K-Nearest Neighbor Algorithm and Case Base Reasoning on Xenia Car Damage Detection Expert System

PT Astra Daihatsu Motor or commonly abbreviated as ADM is the Sole Agent Brand Holder (ATPM) of Daihatsu cars in Indonesia. Xenia car is one of the most popular cars in Indonesia. Although there are many Xenia car users, it is not uncommon for Xenia cars to experience damage caused by the ignorance of car users, where the car user only knows how to use it but does not know how to maintain the car properly and correctly. Before damage occurs to the car, the car usually experiences several symptoms of damage that the user does not realize. With that, there are often difficulties experienced by users to find out the type of damage to the car. The purpose of applying and designing applications in this study is to apply the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to Xenia cars and to design and build applications with the Case Based Reasoning method with the K-Nearest Neighbor Algorithm to detect damage to web-based Xenia cars. This research uses the Research and Development method. Based on the results of research from previous cases, the new case has similarities with 5 cases and the highest similitude value is with the highest type, namely the type of Injector Malfunction damage with a value of 0.625 or around 62.5%. This expert system application can detect and determine the results of Xenia car engine damage detection by applying a method that looks for the closest similarity value of new cases to old cases, namely the Case Based Reasoning method and the K-Nearest Neighbor Algorithm looking for the closest neighbors of the same weight value. This web-based expert system can be used by users to find the results of Xenia Car engine damage detection experienced by determining the symptoms that are available in web-based applications. This web-based application can also provide solutions from the detection results of the type of Xenia car engine damage.