scholarly journals An Expert System for Pneumococcal Prognosis

2018 ◽  
Vol 2 (3-2) ◽  
pp. 204
Author(s):  
Nurnadzirah Othman ◽  
Nureize Arbaiy ◽  
Hamijah Mohd Rahman
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
Knowledge Sharing ◽  
Body Condition ◽  
Pneumococcal Disease ◽  
Preventive Measures ◽  
Child Death ◽  
Disease Diagnosis ◽  
Access To Information ◽  
System Method

Threats and viruses are particularly alarming for children with low immunization levels. Pneumococcal disease is the world's most important cause of child death and has claimed many lives. Since awareness of the dangers of Pneumococcal viruses among parents is low in Malaysia, preventive measures such as vaccine intake cannot be done comprehensively. Hence, in order to communicate information about Pneumococcal disease, a pneumococcal disease diagnosis system for children is developed. This system employs expert system method and apply forward chaining technique for its reasoning. Knowledge base of the system is stored in the database for data management. This alternative system allows access to information as well as early diagnosis of early symptoms can be detected. This system is expected to benefit users in terms of knowledge sharing, and self-checking on their body condition, especially parents, to prevent any possible diseases that may infect children's.

scholarly journals Tuberculosis Disease Diagnosis Expert System Method of Certainty Factor

2020 ◽  
Vol 2 (1) ◽  
pp. 129-134
Author(s):  
Betti Mastaria Br Sembiring ◽  
Paska Marto Hasugian
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
Disease Diagnosis ◽  
Certainty Factor ◽  
Disease Symptoms ◽  
System Method ◽  
Tuberculosis Disease Diagnosis ◽  
Tuberculosis Disease

Nowadays computers are widely used in the medical world to aid in the diagnosis of a disease. The most frequently encountered Penyakityang adalahpenyakitTuberculosis. Therefore, prevention of tuberculosis disease begins with diagnosing dini.Salah a technique in diagnosing tuberculosis disease is an expert system. Therefore research inibertujuan construct an expert system that is used for early diagnosis of Tuberculosis disease by gejalayang in anguish. The system displays the amount of credence to the possibility of disease symptoms yangdiderita users. The value of these beliefs using Certainty Factor, because the CF is able to determine the value of trust in a greater uncertainty and be able to demonstrate absolute confidence.

ANALYSIS OF PLANT FRAGARIA XANANASSA DISEASE DIAGNOSES USING PRODUCTION RULES BASE ON EXPERT SYSTEM

2020 ◽  
Vol 16 (1) ◽  
pp. 25-32
Author(s):  
Basiroh Basiroh ◽  
Wiji Lestari
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
General Public ◽  
Insect Pests ◽  
Fruit Rot ◽  
Proper Treatment ◽  
Harvest Time ◽  
Production Rules

Errors that occur in solving problems in strawberry plants (Fragaria Xananassa) such as the presence of leaf patches, fruit rot, perforated leaves, and insect pests can be the cause of not maximum in harvest time. The farmers and the general public who planted strawberry (Fragaria Xananassa) need to know the proper treatment of diseases and pests so that future yields as expected. Therefore, it takes an application as a solution in the delivery of information related to the problems that are often encountered in strawberry plants (Fragaria Xananassa). Methods of production rules can be used to diagnose the disease strawberry (Fragaria Xananassa) based on signs or symptoms that occur in the parts of plants and strawberry, the results of diagnosis using this method are the same as we do Consultation on experts.  The purpose of this study was to determine the early diagnosis of disease in strawberry plants (Fragaria Xananassa) based on signs or symptoms that occur in the plant and fruit parts. The results of the analysis of this study showed that the validation of disease and symptom data in strawberry plants (Fragaria Xananassa) reached 99%, meaning that between the data of symptoms and disease understudy the accuracy was guaranteed with the experts.

Expert System: Vertigo Disease Diagnosis with Backward Chaining Method

2020 ◽  
Author(s):  
Beki Subaeki ◽  
Shinta Getri Lovelina ◽  
Hanhan Hanafiah Solihin ◽  
SW Pitara ◽  
Ahmad Munandar ◽  
...  
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Backward Chaining

SISTEM PAKAR MENENTUKAN PENYAKIT GINJAL DENGAN METODE FORWARD CHAINING

2020 ◽  
Vol 11 (1) ◽  
pp. 27-32
Author(s):  
Wahyu Alfandry Pulungan
Keyword(s):  
Expert System ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Metabolic System ◽  
Consultation Process ◽  
The Public ◽  
System Disease ◽  
Visual Basic 6.0 ◽  
High Calorie ◽  
Selection Of

Selection of issues regarding the kind of kidney disease as a sample of this study, is the fact that diseases Kidney is an important organ in our body's metabolic system, because the density of activity, we often forget to take care of. Irregular diet, inadequate intake of fiber and mineral water, as well as the consumption of food or drink high calorie instant, unwittingly aggravate the kidneys. Starting from the filtration, reabsorption, to augmentation of nutrients that under to the kidneys via the blood. The purpose of this research is to build an expert system Kidney disease using Visual Basic 6.0 programming language that is capable of providing services to the public and delivery of information related to kidney disease. In this research, data collection is done by using the method of observation, interviews, and literature. From the results of this study indicate that the presence of kidney disease diagnosis expert system in humans can provide significant benefits, among others, the processing of data and consultation process carried out quickly and produce a fairly accurate report, thus making the job more effectively and efficiently. Keywords: Expert System, Disease, Kidney, Human.

scholarly journals Development of a Web Based Expert System for Rubber Crop Disease Diagnosis and Management

2018 ◽  
Vol 10 (3) ◽  
pp. 239-248
Author(s):  
S. Konyeha ◽  
F. A. Imouokhome
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Field Extension ◽  
Rule Base ◽  
Destructive Effect ◽  
Web Based ◽  
Procedural Code ◽  
Base Engine ◽  
Crop Disease ◽  
User Friendly

An expert system imitates the decision–making adeptness of a human expert. They are intended to answer complicated questions characterized mainly as if–then rules instead of traditional procedural code. A major problem facing the cultivation of rubber (Hevea brasiliensis) in developing countries is the destructive effect of pathogens which result in about fifty percent (50%) loss in crop yield. This problem persists, due to a communication gap between agricultural researchers, such that field extension officers, and farmers are hampered by various operational and logistic challenges. This paper is an effort to bridge this gap, and hence features an expert system that can be accessed online by farmers.  The expert system allows farmers to select disease symptoms presented in categories from a JAVA based user friendly graphical interface. The output generated by the rule–base engine, diagnoses the diseases of the rubber crop, and suggests curative and preventive measures. The main source of information for developing the expert system’ knowledge–base was the Rubber Research Institute, Iyanomo, Edo State, Nigeria.

scholarly journals Perancangan Aplikasi Sistem Pakar Penyakit Roseola Dengan Menggunakan Metode Certainty Factor

2020 ◽  
Vol 1 (2) ◽  
pp. 107
Author(s):  
Lola Fida Putri
Keyword(s):  
Expert System ◽  
Early Diagnosis ◽  
Low Income ◽  
Acute Illness ◽  
Brain Inflammation ◽  
Not Given ◽  
Certainty Factor ◽  
Factor Method ◽  
Applied Knowledge

Measles Roseola usually attacks infants with transmission from a sprinkling of sufferers' saliva. Roseola must be treated quickly because it can cause liver and brain inflammation. Roseola's disease for people whose economy is low is not given much attention because it is often diagnosed in severe or acute illness. This is because the red rash in infants is a common measles. Early diagnosis of Roseola's disease is a good way to avoid adverse consequences for the baby's health. The Roseola disease expert system is able to help low-income people to self-diagnose the disease. Roseola's disease expert system is applied knowledge gained from experts, namely specialist dermatologists in children. Processing of symptoms based on facts with the value and calculation of the Certainty Factor method. Certainty Factor determines good results by combining expert values and user values.

scholarly journals Aplikasi Sistem Pakar Diagnosa Penyakit Pada Anak Bawah Lima Tahun Menggunakan Metode Forward Chaining

2017 ◽  
Vol 3 (1) ◽  
pp. 61 ◽  
Author(s):  
Bagus Fery Yanto ◽  
Indah Werdiningsih ◽  
Endah Purwanti
Keyword(s):  
Expert System ◽  
System Application ◽  
Disease Diagnosis ◽  
Information Collection ◽  
Forward Chaining ◽  
Second Stage ◽  
Children Health ◽  
Third Stage ◽  
Testing Data ◽  
Three Stages

Abstrak— Anak-anak pada usia 2 bulan sampai 5 tahun (Balita) lebih rentan terkena penyakit. Lingkungan sangat mempengaruhi kesehatan Balita. Penelitian ini bertujuan untuk membuat sebuah aplikasi sistem pakar diagnosa penyakit pada Balita berbasis mobile. Penelitian ini terdiri dari tiga tahap. Tahap pertama adalah pengumpulan data dan informasi dari Manajemen Terpadu Balita Sakit (MTBS) dan wawancara dengan Bidan. Dari pengumpulan data dan informasi tersebut ditemukan fakta penyakit, keluhan, gejala dan saran penanganan. Tahap kedua adalah pembuatan rule dengan 18 penyakit. Tahap ketiga adalah implementasi aplikasi sistem pakar berbasis mobile dengan fitur diagnosa penyakit, riwayat diagnosa dan kumpulan penyakit. Aplikasi sistem pakar yang dibuat dapat mendiagnosa penyakit dan memberikan saran penanganan. Hasil evaluasi dari 50 data uji coba menghasilkan tingkat akurasi sebesar 82%, dimana 41 hasil diagnosa yang benar dan 9 diagnosa yang salah. Kata Kunci— Sistem Pakar, Forward Chaining, Diagnosa Penyakit, Manajemen Terpadu Balita Sakit, Knowladge BaseAbstract— Children at the age of 2 months to 5 years (toddlers) are more susceptible to disease contagious. Environmental condition significantly influences the children health. This  research aimed to create a mobile-based expert system application to diagnose disease in toddlers. This research consist of three stages. The first stage were data and information collection from Manajemen Terpadu Balita Sakit  (MTBS) and interview with medical staffs. From the first stage, we can discover the disease facts, signs, symptoms and treatment advices. The second stage was the construction of rules for 18 diseases. The third stage was the implementation of mobile-based expert system application with features of disease diagnosis, diagnosis history and collection of disease diagnosis. Expert system application made able to diagnose the disease and provide treatment advice. The results of evaluation using 50 testing data provides the level of accuracy of 82%, where 41 diagnosis result were true and 9 diagnosis were false. Keywords— Expert System, Forward Chaining, Disease Diagnosis, Manajemen Terpadu Balita Sakit, Knowledge Base

scholarly journals SISTEM PAKAR DIAGNOSA PENYAKIT DAN HAMA PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAIVE BAYES

2021 ◽  
Vol 2 (3) ◽  
pp. 390-398
Author(s):  
Bayu Bastiyan Suherman
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Preventive Measures ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Agricultural Commodities ◽  
Bayes Method ◽  
Mathematical Basis ◽  
Lack Of Information ◽  
Corn Plants

Corn is one of the leading agricultural commodities that can be used as a staple plant other than rice. Constraints faced by corn farmers include the lack of information about diseases that attack the corn plants, which causes less productivity. In this study a system was developed that can automatically detect disease that attacks corn plants so that preventive measures can be taken to prevent corn plants from dying. Expert systems are designed to solve certain problems by imitating the work of experts. In addition, this expert system also helps farmers who are experiencing problems regarding diseases and pests and their solutions without relying on an expert. The method used is the Naive Bayes method, Naive Bayes is a method used to predict probabilities and has several characteristics that are istitively in accordance with the way of thinking of an expert and accompanied by a strong mathematical basis. From the tests carried out with diagnoses obtained from the comparison between the results of expert diagnoses and the diagnosis of the system to diagnose diseases and pests in corn plants is 90%.

scholarly journals Identifying Severe Malnutrition in Children with an Expert System

2021 ◽  
pp. 15-20
Author(s):  
Devia Kartika ◽  
Rima Liana Gema ◽  
Mutiana Pratiwi
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Computer Program ◽  
System Application ◽  
Nutrition Status ◽  
Easy Access ◽  
Severe Malnutrition ◽  
Inference Method ◽  
Human Expert ◽  
System Method

Expert system is a computer program which is designed for modelling the ability of problem solving as it is an expert (human expert). The expert system method used is the forward chaining method which is the inference method that is doing logical reasoning from the problem to its solution. The aim of this research is to design and develop an expert system that is able to identify the severe malnutrition on children from the age of 0 - 5 years old. The knowledge is derived from the question askedto a nutrition expert. The data are taken from the questions asked to the user and when all of the questions has been answered, then the goal will be appeared which shows the nutrition status. This system application will enable the user to diagnose the nutrition/disease that affects children and get the solution. This system can be used by any kind of user due to the easy access. This system is also put the important information about the severe malnutrition and the recent news of children’s health so it will add more knowledge for the parents about the importance of severe malnutrition’s prevention.

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