Expert System of Quail Disease Diagnosis using Forward Chaining Method

2017 ◽  
Vol 5 (1) ◽  
pp. 206 ◽  
Author(s):  
B. Herawan Hayadi ◽  
Kasman Rukun ◽  
Rizky Ema Wulansari ◽  
Tutut Herawan ◽  
Dahliyusmanto Dahliyusmanto ◽  
...  
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Coverage Area ◽  
Great Demand ◽  
Forward Chaining ◽  
The Many

<p class="Normal1">Expert system applications were in great demand in various circles since 1950, with a coverage area that was large. Expert System on the organization was aimed at adding value, increasing productivity as well as the area of managerial can make decisions quickly and accurately. Neither with organizations that did business quail, which was very promising, but needed to be alert for the presence of disease in quail healthy, as in the case in birds quail were highly vulnerable to various kinds of diseases caused by viruses or bacteria. the benefits of the expert system that was able to diagnose quickly and accurately to the symptoms of the disease caused was expected to helped the farmers in of anticipation the many losses caused by disease. Required accuracy and the accuracy of the counting in diagnosing the symptoms of the disease in order to summarized the results by using forward chaining method.</p>

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 Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis

2018 ◽  
Vol 5 (1) ◽  
pp. 57 ◽  
Author(s):  
Abdul Muis Alfatah ◽  
Riza Arifudin ◽  
Much Aziz Muslim
Keyword(s):  
Expert System ◽  
Decision Tree ◽  
Lung Disease ◽  
Medical Record ◽  
Computer System ◽  
Disease Diagnosis ◽  
Forward Chaining

The expert system is a computer system that contains set of rules to solve problems like an expert. The lungs are one of the vulnerable respiratory organs. The purpose of this research is to implement decision tree and dempster shafer method on lung disease diagnosis and measure the accuracy of the system. The symptom was searched using forward chaining decision tree and the diagnosis was calculated using dempster shafer method. Dempster Shafer method calculates the possibility of a lung disease based on the density of probability value that possessed by each symptom. This research used 65 data obtained from medical record of Puskesmas Tegowanu Grobogan Regency. General symptoms and types of disease are used as a variable. Based on the results of the study, it can be concluded that the results of the diagnosis using dempster shafer method has an 83.08% accuracy.

scholarly journals Implementasi Metode Certainty Factor pada Sistem Pakar Diagnosa Penyakit Ayam Berbasis Android

2019 ◽  
Vol 5 (3) ◽  
pp. 185
Author(s):  
Muqorobin Muqorobin ◽  
Prabowo Budi Utomo ◽  
Muhammad Nafi’Uddin ◽  
Kusrini Kusrini
Keyword(s):  
Expert System ◽  
Mobile Application ◽  
Expert Knowledge ◽  
Disease Diagnosis ◽  
Android Application ◽  
Certainty Factor ◽  
Web Based ◽  
Diagnosis System ◽  
Forward Chaining ◽  
Web Based System

Penelitian ini dilakukan berdasarkan kebutuhan akan adanya alat bantu bagi peternak maupun penyuluh dalam mendiagnosis penyakit pada ayam. Basis pengetahuan sepenuhnya diambil dari pengetahuan pakar yang dapat mendiagnosa dan menentukan nama penyakit yang diderita oleh ayam. Penelitian ini dibuat berdasarkan hasil analisis dengan membandingkan 4 jurnal internasional yang berjudul “Expert system of quail disease diagnosis using forward chaining method, An Expert System for Management of Poultry Diseases, Developling Mobile Expert Web-based System Using Brainstroming Method, Disease Diagnosis System”. Berdasarkan keempat jurnal tersebut dapat dikembangkan inovasi baru berupa Sistem pakar diagnosa penyakit ayam menggunakan metode Certainty Factor. Metodologi penelitian menggunakan wawancara dan studi literature sehigga dapat menggumpulkan data yang lebih lengkap. Sistem Pakar ini akan di implementasikan kedalam sebuah aplikasi mobile berbasis android dengan harapan memudahkan user dalam menggunakan karena dibuat kedalam aplikasi android sehingga bisa di install dalam handphone. Hasil akhir berupa suatu informasi data penyakit dengan nilai Certainty Factor/kepastian.Kata Kunci — Diagnosa Penyakit Ayam, Sistem Pakar, Android, Certainty FectorThis study was conducted based on the need for tools for farmers and extension workers in diagnosingdiseases in chickens. The knowledge base is completely drawn from the expert knowledge that can diagnose and determine the name of the disease suffered by chickens. This study was based on the results of the analysis by comparing four international journals entitled "Expert system of quail disease diagnosis using forward chaining method, An Expert System for Management of Poultry Diseases, Developing Mobile Expert Web-based System Using Brainstroming Method, Disease Diagnosis System". Based on the four journals can be developed a new innovation in the form of expert system of chicken disease diagnosis using Certainty Factor method. The research methodology uses interviews and literature studies so that it can collect more complete data. Expert System will be implemented into an android-based mobile application with the hope of facilitating the user in using because it is made into the android application that can be installed in the mobile phone. The final result is an information of disease data with Certainty Factor value/certainty.Keywords — Diagnosis of Chicken Disease, Expert System, Android, Certainty Fector

Design of an Android-Based Tropical Disease Diagnosis Expert System Design Using a Combined Method of Forward Chanining and Backward Chaining

2015 ◽  
Vol 1 (1) ◽  
pp. 43-50
Author(s):  
Muhammad Fahmi Hidayah
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Disease Diagnosis ◽  
Reference Book ◽  
Combined Method ◽  
Specific Domain ◽  
Backward Chaining ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Specific Symptoms

A doctor or medical scholar needs a reference book to learn how to diagnose tropical diseases. This reference book is sometimes a hassle if you have to carry it everywhere. This reference book is also impractical if you have to search it first to find the symptoms and diseases you want to study. So that we need a system to make it easier for doctors and medical scholars to study the science of diagnosis and look for symptoms and diseases. Expert systems are knowledge-based programs that provide expert quality solutions to problems in a specific domain. This expert system is used in the fields of medicine, agriculture, business, and others. Expert systems in the field of medicine make it easy to identify diseases suffered by patients through the symptoms present in the patient. This expert system helps doctors make diagnoses to convince doctors about the results of the diagnosis. The expert system in this study uses a combined method. The combined method is forward chaining and backward chaining. The forward chaining method is used to determine specific symptoms that appear, while the backward chaining method is used to trace general symptoms that arise from specific symptoms that have been previously selected. The result of combining these methods provides a diagnostic percentage of 100%. Meanwhile, the user's assessment of the system gives a good response.

scholarly journals Expert system for disease diagnosis in cocoa plant using android-based forward chaining method

2019 ◽  
Vol 1339 ◽  
pp. 012009
Author(s):  
Vicky Ariandi ◽  
Hezy Kurnia ◽  
Heriyanto ◽  
Hilda Marry
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Forward Chaining

scholarly journals Expert System for Diagnosis Chicken Disease using Bayes Theorem

2019 ◽  
Author(s):  
HENGKI TAMANDO SIHOTANG
Keyword(s):  
Expert System ◽  
Programming Language ◽  
Visual Basic ◽  
Bayes Theorem ◽  
Disease Diagnosis ◽  
The Body ◽  
Human Knowledge ◽  
Inference Process ◽  
Forward Chaining

Chicken disease is a condition in which the body organs of chickens cannot function normally. Diagnosing a disease requires symptoms that appear on the chicken's body. To conduct a disease diagnosis, further examination is needed by specialists (experts). An expert system is a system that uses human knowledge that is entered into a computer to solve problems that are usually resolved by experts. The system created in solving problems uses the Bayes Theorem method in which the inference process uses Forward Chaining. The application was developed using the visual basic 2010 programming language and MySQL database.

scholarly journals Pengembangan Sistem Pakar Berbasis Android untuk Menentukan Obat Generik pada Penyakit Kulit Menggunakan Metode Forward Chaining

2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Rinanza Zulmy Alhamri ◽  
Abidatul Izzah ◽  
Kunti Eliyen
Keyword(s):  
Expert System ◽  
Skin Disease ◽  
Skin Diseases ◽  
Generic Drugs ◽  
Disease Diagnosis ◽  
Generic Medicine ◽  
Design System ◽  
Common Disease ◽  
Forward Chaining ◽  
Analysis System

Skin disease can be suffered by all people and ages as a common disease. In general treatment for people with skin diseases is by consulting to medical experts and asking for a medicine prescription. However, by utilizing current communication technology, sufferers are able to get good information about skin diseases. The expert system for the diagnosis of skin diseases has been done before. However, the expert system is built based on web and desktop, so it is less flexible in use, moreover in supporting self assistance for the skin disease sufferer. Therefore, this study aims to develop an Android-based expert system that can help diagnose skin diseases in humans as well as provide recommendations of generic medicine as first aid. The expert system developed by implementing the Forward Chaining (FC) method as an inference technique. This research was conducted in five phases, namely data collection, analysis system, design system, implementation, and testing. The knowledge base in this expert system includes 39 types of skin diseases, 83 symptoms, 16 types of generic drugs, 150 lines rules of skin disease diagnosis, and 39 lines recommendations of generic drug.

scholarly journals Design of the expert system to analyze disease in Plant Teak using Forward Chaining

2017 ◽  
Vol 1 (1) ◽  
pp. 11
Author(s):  
Poningsih Poningsih
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Economic Value ◽  
Disease Diagnosis ◽  
High Quality ◽  
Web Based ◽  
Community Forests ◽  
Forward Chaining ◽  
Teak Wood

Teak is one kind of plant that is already widely known and developed by the wider community in the form of plantations and community forests. This is because until now Teak wood is a commodity of luxury, high quality, the price is expensive, and high economic value. Expert systems are a part of the method sciences artificial intelligence to make an application program disease diagnosis teak computerized seek to replace and mimic the reasoning process of an expert or experts in solving the problem specification that can be said to be a duplicate from an expert because science knowledge is stored inside a database  Expert System for the diagnosis of disease teak using forward chaining method aims to explore the characteristics shown in the form of questions in order to diagnose the disease teak with web-based software. Device keel expert system can recognize the disease after consulting identity by answering some of the questions presented by the application of expert systems and can infer some kind of disease in plants teak. Data disease known customize rules (rules) are made to match the characteristics of teak disease and provide treatment solutions.

scholarly journals Sistem Pakar Deteksi Penyakit pada Anak Menggunakan Metode Forward Chaining

2020 ◽  
Author(s):  
Meilinda Sari ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Expert System ◽  
Decision Rules ◽  
Working Hours ◽  
Childhood Diseases ◽  
Forward Chaining ◽  
Number Of Patients ◽  
Children's Diseases ◽  
System Calculation ◽  
The Many ◽  
Decision Tables

Health is the most valuable thing for humans, because anyone is vulnerable to health problems. Especially in children, children are very susceptible to germs and sensitivity to symptoms of a disease is a fear for parents themselves. However, with the convenience of having an expert doctor, sometimes there are also weaknesses such as limited working hours or doctor's practice hours and the number of patients who have to wait for queues and also the many parents who do not know about the symptoms and types of children's diseases, a system is built to facilitate the medical team and system users. The purpose of this study was to detect children's diseases using the Forward Chaining method precisely and accurately. The data that were processed were 25 symptoms and 5 types of childhood diseases which were sourced from patient medical records and interviews with experts at the Ibnu Sina Simpang Empat Islamic Hospital. The symptoms and types of disease are entered into the Expert System using the rules of rules and the Forward Chaining method. To diagnose a child's disease, a Forward Chaining method is needed with the following stages: Preparing input data, determining decision tables, determining rules, tracking processes, making decision trees. The results of the study with 25 symptom data obtained as many as 5 decision rules, namely which type of childhood disease the patient has and the initial treatment that must be done. Based on the analysis carried out, it can be seen the types of diseases suffered by children so that it can be used as a reference for making decisions to diagnose diseases in children. This expert system calculation shows the percentage of success from the expert.

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