scholarly journals SISTEM PAKAR DIAGNOSA PENYAKIT SALURAN PERNAFASAN DENGAN METODE FUZZY TSUKAMOTO

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Dhevi Dadi Kusumaningtyas ◽  
Muhammad Hasbi ◽  
Hendro Wijayanto
Keyword(s):  
Expert System ◽  
Respiratory Disease ◽  
Respiratory Diseases ◽  
Good Description ◽  
Disease Diagnosis ◽  
Diagnostic Process ◽  
Good Information ◽  
Disease Information ◽  
Binary Tree Structure ◽  
User Friendly

Respiratory diseases are one of the most common diseases in Indonesia. Respiratory diseases increase the risk of fatal if not treated immediately. However, it is unfortunate that knowledge about the risk of respiratory disease is still lacking. The search method used in making this expert system is forward chaining with binary tree structure. Namely doing the processing of a set of data, then conducted inference in accordance with the rules applied to find the optimal conclusion. Experts provide rules for determining symptoms and illness. While the calculation and ranking of diseases that may suffer patients using the method fuzzy tsukamoto to provide the results of calculations that are certain based on the parameters. Then the patient's diagnostic process is done by the system. The Diagnostic Expert System for Respiratory Disease has been successfully established and can be used to assist in estimating the illness suffered by the patient as the result of the developed system is not much different from the running system. Based on the comparison of disease diagnosis result in expert system with manual system then the system accuracy level is 90,9%. Based on the website view has the largest percentage of 71.42 in good description, for user friendly / ease of respiratory system experts get the largest percentage of 85.71 in good information, to assist in the process of disease information and treatment get the largest percentage of 57.14 in a good description, to help the diagnosis process becomes easier to get the largest percentage of 71.42 in good information, for this expert system provides information on respiratory disease treatment accurately get the largest percentage of 57.14 in either.

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.

Application Research of Neural Expert System on Diseases and Insects of Fruit Tree

2014 ◽  
Vol 543-547 ◽  
pp. 4161-4164
Author(s):  
Hong Juan Li ◽  
Shu Mei Zhang
Keyword(s):  
Neural Networks ◽  
Expert System ◽  
Prediction Models ◽  
Growth Management ◽  
Fruit Trees ◽  
Disease Diagnosis ◽  
Fruit Tree ◽  
Learning Ability ◽  
Diagnostic Process ◽  
Management Decision

Information technology includes neural networks, ontology technology, expert system, and so on, and the growth model can predict and manage growth conditions of fruit trees. The traditional expert system has shortcomings of poor self-learning ability, so the improved expert system is used to perform diagnosis of diseases and insects of fruit tree. Firstly the ontology is used to collect related symptoms of diseases and insects of fruit trees, the expert system and neural network are combined to build the prediction model of diseases and insects of fruit tree, then the conclusions of the diagnostic process are regarded as the input neurons and output neurons of neural networks, and are diagnosed by expert, so the prediction models of disease diagnosis of fruit trees are made. The models can implement the function of expert diagnosis and prediction, and provide technical support and management decision for the growth management of fruit tree, greatly improving the diagnosis efficiency of diseases and insects of fruit tree.

Therapeutic role of vegetables in Respiratory Diseases – A critical review from Ayurvedic classics.

2016 ◽  
Vol 1 (3) ◽  
Author(s):  
Dr. Raghavendra Naik ◽  
Shweta Vekariya ◽  
R. N. Acharya ◽  
Sneha D. Borkar
Keyword(s):  
Clinical Practice ◽  
Respiratory Disease ◽  
Respiratory System ◽  
Critical Review ◽  
Critical Analysis ◽  
Respiratory Diseases ◽  
Unique Contribution ◽  
Pharmacological Activities ◽  
The Family

The concept of Pathya (wholesome diet) is an unique contribution of Ayurveda, which plays an important role in prevention and management of many diseases. “Shakavarga”, a category under dietetics in classical texts of Ayurveda enlisted different vegetables with their properties and indications in different disease conditions. These vegetables can be prescribed as Pathya (wholesome diet) in clinical practice. In the present review, plants described under Shakavarga, indicated as Pathya in different diseases related to Pranavaha Srotas (Respiratory system) were compiled from 15 different Ayurvedic classical texts. Critical analysis of the compiled data reveals that out of 332 vegetables described under Shakavarga, 44 are indicated in respiratory disease like Shvasa (Dyspnoea/Asthma), Kasa (Cough), Peenasa (Chronic rhinitis) and Hikka (Hiccup). Among them, botanical identity of 42 classical plants has been established and maximum number of vegetables belongs to the family cucurbitaceae (10) followed by solanaceae (4). Some of these vegetables have been reported for their various pharmacological activities related to prevention and management of diseases related to Pranavaha Srotas (Respiratory system). These vegetables are reported for their anti-inflammatory (16), antioxidant (14), anti-allergic (6) and antitussive (3) activities. The observed result may be helpful in use of vegetables as Pathya (wholesome diet) and planning further scientific studies about the efficacy of these plants on prevention as well as management of respiratory diseases.

scholarly journals S2K Guideline for Diagnosis of Idiopathic Pulmonary Fibrosis

Respiration ◽  
2021 ◽  
pp. 1-34
Author(s):  
Jürgen Behr ◽  
Andreas Günther ◽  
Francesco Bonella ◽  
Julien Dinkel ◽  
Ludger Fink ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Disease Diagnosis ◽  
Diagnostic Process ◽  
High Resolution Computed Tomography ◽  
Cellular Analysis ◽  
Golden Standard ◽  
Technical Advances ◽  
Transbronchial Lung Cryobiopsy ◽  
Effective Diagnosis

Idiopathic pulmonary fibrosis (IPF) is a severe and often fatal disease. Diagnosis of IPF requires considerable expertise and experience. Since the publication of the international IPF guideline in the year 2011 and the update 2018 several studies and technical advances have occurred, which made a new assessment of the diagnostic process mandatory. The goal of this guideline is to foster early, confident, and effective diagnosis of IPF. The guideline focusses on the typical clinical context of an IPF patient and provides tools to exclude known causes of interstitial lung disease including standardized questionnaires, serologic testing, and cellular analysis of bronchoalveolar lavage. High-resolution computed tomography remains crucial in the diagnostic workup. If it is necessary to obtain specimens for histology, transbronchial lung cryobiopsy is the primary approach, while surgical lung biopsy is reserved for patients who are fit for it and in whom a bronchoscopic diagnosis did not provide the information needed. After all, IPF is a diagnosis of exclusion and multidisciplinary discussion remains the golden standard of diagnosis.

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 Osteoporosis Risk Prediction Using Data Mining Algorithms

2020 ◽  
Author(s):  
Efat Jabarpour ◽  
Amin Abedini ◽  
Abbasali Keshtkar
Keyword(s):  
Data Mining ◽  
Personal Information ◽  
Disease Diagnosis ◽  
Support Vector ◽  
Data Mining Algorithms ◽  
Industry Standard ◽  
Disease Information ◽  
Increased Risk ◽  
Using Data ◽  
Mining Algorithms

Introduction: Osteoporosis is a disease that reduces bone density and loses the quality of bone microstructure leading to an increased risk of fractures. It is one of the major causes of inability and death in elderly people. The current study aims at determining the factors influencing the incidence of osteoporosis and providing a predictive model for the disease diagnosis to increase the diagnostic speed and reduce diagnostic costs. Methods: An Individual's data including personal information, lifestyle, and disease information were reviewed. A new model has been presented based on the Cross-Industry Standard Process CRISP methodology. Besides, Support Vector Machine (SVM) and Bayes methods (Tree Augmented Naïve Bayes (TAN)) and Clementine12 have been used as data mining tools. Results: Some features have been detected to affect this disease. The rules have been extracted that can be used as a pattern for the prediction of the patients' status. Classification precision was calculated to be 88.39% for SVM, and 91.29% for  (TAN) when the precision of  TAN  is higher comparing to other methods. Conclusion: The most effective factors concerning osteoporosis are detected and can be used for a new sample with defined characteristics to predict the possibility of osteoporosis in a person.  

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 MODEL PENUNJANG KEPUTUSAN INVESTASI BAGI PENGEMBANGAN AGROINDUSTRI PERIKANAN

2016 ◽  
Vol 13 (3) ◽  
Author(s):  
Bambang Herry Purnomo
Keyword(s):  
Expert System ◽  
Fuzzy Expert System ◽  
Interface Model ◽  
User Friendly

Investasi mempunyai peranan penting dalam menumbuhkembangkan agroindustri perikanan. Model penunjang keputusan investasi diperlukan dalam rangka membantu pemerintah daerah mengambil keputusan investasi agroindustri perikanan secara cepat dan tepat. Kajian ini bertujuan merancangbangun Sistem Manajemen Ahli untuk menunjang keputusan investasi dengan menggunakan pendekatan wilayah bagi pengembangan agroindustri perikanan dan kelembagaannya.  Sistem terdiri dari 6 model, yaitu (1)  fuzzy expert system untuk menentukan wilayah pengembangan, (2)  model untuk menentukan komoditas perikanan unggulan, (3) model  untuk menentukan produk unggulan, (4) model untuk menentukan potensi bahan baku, (5) model   analisis kelayakan finansial proyek agroindustri, dan (6) model untuk menentukan bentuk kelembagaan bagi pengembangan usaha kecil perikanan. Verifikasi model dilakukan di Kabupaten Tuban, Jawa Timur. Contoh hasil verifikasi menunjukkan bahwa wilayah pengembangan yang terpilih adalah Kecamatan Palang dengan komoditas utamanya ikan teri dan produk unggulannya ikan teri asin. Potensi bahan baku ikan teri pada tahun 2010 yang dapat dimanfaatkan oleh proyek agroindustri di wilayah ini adalah 1067 ton. Kajian lebih lanjut yang disarankan adalah penggunaan model dinamis untuk menduga produksi ikan teri dan pengembangan interface model penunjang keputusan yang lebih fleksibel dan user friendly.

Sign in / Sign up

Export Citation Format

Share Document