Web-based Expert System Research Articles

Sistem Pakar untuk Mendiagnosa Penyakit Tanaman Cabai Menggunakan Metode Forward Chaining

Chilli farming is an important sector in Ende District, but plant disease problems are often an obstacle that hampers productivity. Farmers often have difficulty recognizing the symptoms of disease in chili plants and determining appropriate treatment steps. To overcome this problem, this research aims to design and build a web-based expert system that can help diagnose chili plant diseases using the Forward Chaining method. This expert system was developed by collecting knowledge from agricultural experts and literature related to chili plant diseases, as well as applying the Forward Chaining method for the reasoning process. Users, especially farmers, can enter the symptoms experienced by chili plants into the system, then the system will produce a disease diagnosis and appropriate treatment recommendations based on these symptoms. This research uses a case study at Maju Tani Agriculture in Ende District to ensure that the expert system developed is relevant to local conditions. This system is implemented in the form of a web-based application so that it can be accessed easily by farmers using devices connected to the internet. The test results show that this expert system can provide accurate and efficient diagnoses, as well as assist farmers in making decisions to overcome chili plant disease problems. It is hoped that this system can increase agricultural productivity and reduce the risk of losses due to plant diseases.

Expert System For Diagnosis of Mental Health Disorders in Students Using Case-Based Reasoning Method With a Web-Based Positive Psychology Approach

Mental health issues among students have become a significant concern affecting their quality of life and academic performance. An effective expert system is needed to diagnose and provide appropriate interventions. This research develops a web-based expert system that utilizes the Case-Based Reasoning (CBR) method combined with a positive psychology approach to diagnose mental health disorders in students. The CBR method identifies similarities between new and previous cases, while the positive psychology approach focuses on individual strengths and potential for growth. The system integrates a database of student mental health cases and CBR algorithms to produce relevant diagnoses. This study investigates four types of mental health disorders: panic, anxiety, stress, and depression. The method used for data analysis is Case-Based Reasoning. The diagnosis results are based on calculations from symptom choices within the system, where each symptom has a weight. The highest similarity calculation obtained from past cases is used as a solution to address the problem. System testing, based on expert knowledge with 15 test data samples categorized by mental health disorders and 38 symptoms, achieved an accuracy rate of 85%.

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.

Metode Forward Chaining untuk Diagnosa dan Penanganan Penyakit Stroke dengan Sistem Pakar

This research aims to develop a web-based expert system with the Forward Chaining method that can diagnose and provide treatment for people with stroke disease. The expert system will be used to help the diagnosis process by analyzing the symptoms reported by the patient. The Forward Chaining method will be used as an inference approach in this expert system. The system will use a knowledge base that contains medical rules obtained from experts. The inference process will be carried out by linking the symptoms reported by the patient with the information in the knowledge base to determine possible diagnoses and appropriate treatments. This expert system will be implemented in the form of a web-based application that can be accessed by the general public. The results of this study show that the expert system to diagnose and provide treatment using the forward chaining method is successfully built and the application can be used to help the general public diagnose by entering the symptoms felt and the expert system will provide diagnostic results and provide treatment.

Diagnosa Penyakit Kanker Prostat menggunakan Metode Certainty Factor

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.

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.

Development of a Web-Based Expert System for Diagnosing Cocoa Diseases Using Forward Chaining and Certainty Factor Methods

Cocoa plant diseases have a detrimental impact on farmers and cultivators. This is due to the limited number and working hours of cocoa plant experts. Another thing is that there are quite a lot of farmers who want to consult, which results in less than optimal handling of cocoa diseases. Therefore, researchers developed an expert system to help diagnose and provide solutions based on disease symptoms experienced by cocoa plants, so that farmers do not need to consult directly with experts. This research uses the forward chaining method in preparing rules and adds the certainty factor (CF) method to calculate the certainty value so that the resulting decisions are more accurate. From the results of manual calculations using a sample of one disease with code P1, the trial showed an accuracy value of 93.0736%. Apart from that, the system was proven to work well and was able to make diagnoses based on symptoms on cocoa plants.

Web-based skin disease diagnosis expert system

. In tropical nations, such as Indonesia, skin diseases are a common ailment. Skin conditions are typically not lethal illnesses, thus patients frequently disregard them and don't take them seriously. Skin conditions can, however, become uncomfortable and threaten the sufferer's survival if they are left untreated for an extended period of time. The result of this research is the creation of a web-based expert system for identifying skin disorders, which can aid in more accurate and timely diagnosis of skin diseases as well as offer treatment advice. The development of a web-based expert system for diagnosing skin diseases uses the forward chaining method. While the development methodology uses ESDLC (Expert System Development Life Cycle), with the phases of Assessment, Knowledge Acquisition, Design, Test, Documentation, and Maintenance

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.

Training on Early Detection of Chronic Energy Deficiency in Pregnancy

Chronic Energy Deficiency in pregnancy is a condition where pregnant women suffer from a lack of food that lasts for a long time. Pregnant women with chronic energy deficiency have poor eating behavior, which is influenced by knowledge, perception, beliefs and health education. Health education provided by health workers can increase knowledge and change eating behavior and can be done better if assisted by an expert system. The aim of this activity is to train health workers (doctors, midwives, nutritionists) to carry out early detection of chronic energy deficiency in pregnancy using an expert system, increasing knowledge, attitudes and eating behavior of pregnant women. The method that will be carried out is training using the web-based expert system modelangraini.com for health workers, health education for pregnant women, and increasing knowledge and changing eating behavior of pregnant women. This activity was carried out for 1 day and took place in Faculty of Medicine, University of Lampung on Saturday 30 September 2023 with 45 family doctors, midwives and nutritionists in Bandar Lampung City participating. The results of the evaluation of the implementation of the service showed that there was an increase in participants' understanding by 91.1% to good understanding, 8.9% of participants had a fairly good understanding, and no participants had a poor understanding of the causes, risk factors, impacts, prevention methods, and early detection of chronic energy deficiency in pregnancy with techniques that are fast, easy and can help health workers in providing education and interventions on the eating behavior of pregnant women. This training activity can improve the skills of health workers in an effort to increase knowledge, attitudes and eating behavior of pregnant women so that they can prevent, overcome and help reduce the prevalence of chronic energy deficiency in pregnant women and prevent stunting in toddlers. Keywords: early detection, chronic energy deficiency, training, health workers

Sistem Pakar untuk Diagnosis Rinitis pada Anak menggunakan Metode Certainty Factor

Expert systems can assist an expert in making decisions that are realized in the form of a program. At this time the program is very helpful in improving various fields such as health, by managing the information that has been obtained. In this research, rhinitis is raised as a topic of discussion by working with experts who are experts in the field, after collecting data through interviews, the conclusion is obtained, namely how to determine whether someone has one of the three types of rhinitis (allergic rhinitis, bacterial rhinitis, and viral rhinitis) with the symptoms experienced and with a fast and accurate process. By using the certainty factor method and applying it to a web-based expert system, it makes it easier for patients and experts to solve the problem, there are 31 types of symptoms among the three types of rhinitis diseases that are used as the basis for the expert system after that with data from 20 patients at the hospital who suffer from various symptoms of rhinitis who have been diagnosed with the disease by experts as validation data and trials it is found that the system is 100% successful in accurately diagnosing each disease in all these patients.

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.

Implementasi Metode Dempster-Shafer Untuk Deteksi Kesehatan Mental Pada Mahasiswa Berbasis Web

Mental health is a person's soul condition to budaptasi in its environment to feel happy or get the comfort of life, so as not to experience mental disorders. Often mental health is ignored by most people because it is different from physical health that can be seen directly with the eyes and can be identified easily. Lack of awareness of mental health in the life of the people of Indonesia and the assumption that a person who goes to psychologists is a person inseasonable, often the individual who actually undergoes mental health problems reluctant to get help from experts or deny that he does not have mental health problems. Limitations of time and costs are also one of the constraints of a student reluctant to get help from experts like psychologists. Therefore, a web-based expert system is built with a dempster-shafer method to use as detection on the student and allows the user to know whether the user has a tendency of the problem on its mental health or not before the official consultation is required from the expert. Testing Accuracy Comparison System between the results of the system and experts by using 100 correspondents from students at Muhammadiyah Magelang University (UNIMMA) 89% know mental health and 65% have experienced mental disorders. The results of the SRQ29 data used and were spread among campus students, this study has used 20 sample data and produces 70% expert suit compliance. From the results of expert suitability obtained from the calculation of the system by selecting symptoms and automatically the system will calculate the accuracy of the existing Belief Valident in every symptom. Then the system will take decisions based on the results of the largest calculation value.

The Empirical Study On Algorithm Optimization In Expert Systems For Diagnosing Rice Plant Diseases

Rice is one of the most important cultivated plants for human survival. The activity of cultivating rice plants becomes a livelihood for most of these residents, so the success rate of the amount of rice harvested becomes very important because they depend on how much rice can be harvested, disease diagnosis is very important for farmers, this is very important to reduce economic losses due to diseases that cause crop failure. Therefore, when dealing with rice diseases, an expert is needed to make diagnoses or solutions to rice diseases. However, an expert does not know when to come to the village, and farmers also do not understand all rice diseases. Therefore, a web-based expert system application using the forward chaining method is proposed to represent an expert to help farmers diagnose and solve diseases of rice plants with existing symptoms.

IMPLEMENTASI SISTEM PAKAR BERBASIS WEB UNTUK MENDIAGNOSIS PENYAKIT AYAM BROILER MENGGUNAKAN METODE FORWARD CHAINING

The expert system is a computer program designed to transfer knowledge from an expert in a specific field to solve problems or provide advice. Its development has led to various applications, including veterinary medicine. This research focuses on implementing a web-based expert system using PHP to assist broiler chicken farmers in diagnosing diseases through forward chaining. The method is a qualitative approach with the waterfall development method and black-box testing, Unified Modeling Language (UML) for system modeling and design. The system, built with PHP, Codeigniter framework, and MariaDB MySQL database, successfully provides a web-based expert application for diagnosing broiler chicken diseases through forward chaining. This application help farmers in effectively diagnosing and managing diseases in their broiler chickens.

Retracted: An Educational Web-Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

Retracted: An Educational Web-Based Expert System for Novice Highway Technology in Flexible Pavement Maintenance

PERANCANGAN SISTEM PAKAR DALAM MENDIAGNOSA KERUSAKAN CCTV BERBASIS WEB MENGGUNAKAN METODE FORWARD CHAINING (STUDI KASUS: PT.MNC PICTURES)

The use of Closed Circuit Television (CCTV) has almost become a common necessity in the current era, especially for security, where it is to record an incident 24 hours a day which can be immediately broadcast or stored as evidence if one day it is needed. Closed Circuit Television or better known as CCTV is equipment that functions to record events in real time in a room. The research objective is to build a web-based expert system that is able to diagnose damage to CCTV and implement the forward chaining method. Data collection methods are observation, interviews and literature study. Meanwhile, the research method used is forward chaining. The result is that an expert system can be built on a web basis and is able to diagnose damage to CCTV and also the forward chaining method can be implemented to overcome the uncertainty of the expert system diagnosis results.

Forward Chaining Algorithm on Informatics Graduate Job Recommendation System Based on MBTI Test

The Myers-Briggs Type Indicator (MBTI) is a method for identifying an individual's personality type based on the psychological theory of Carl Gustav Jung. In the context of computer science students, they often face challenges in planning their academic journey and determining the direction of their career development during their studies, causing confusion when it comes to choosing a career path in the field of computer science in the future. To address these challenges, the researcher has developed a web-based expert system using the PHP programming language. This expert system is designed to make decisions based on a collection of user responses, which are processed using the forward chaining method, ultimately providing the user's personality type along with suitable career choices. The primary objective of the expert system is to assist students in making decisions regarding their studies and future careers. Through this research, the researcher has produced a functioning website capable of efficiently processing user responses and generating decisions regarding personality types and career options. Thus, this study provides a solution to aid computer science students in planning their academic and career paths.