scholarly journals Perancangan Sistem Diagnosa Penyakit Campak Dengan Menggunakan Certainty Factor

2021 ◽  
Vol 6 (2) ◽  
pp. 96
Author(s):  
I Wayan Rangga Pinastawa ◽  
Ema Utami ◽  
M. Rudyanto Arief
Keyword(s):  
Expert System ◽  
System Design ◽  
Disease Diagnosis ◽  
Design System ◽  
Rule Base ◽  
Certainty Factor ◽  
Activity Diagram ◽  
System Disease ◽  
Engine Design ◽  
Output System

Penyakit campak merupakan salah satu penyakit menular yang masih menjadi masalah kesehatan di Indonesia, karena sering dilaporkan dibeberapa daerah. Menurut data IDAI insiden campak pada balita sebesar 582/10.000. Metode yang digunakan adalah metode Certainty Factor atau Metode Kepastian. Tujuan penelitian ini adalah membuat perangkat lunak sistem pakar yang diharapkan dapat membantu masyarakat dalam mendiagnosa jenis penyakit campak dan rubella. Perangkat lunak sistem pakar ini meliputi analisis kebutuhan user, analisis kebutuhan sistem dan perancangan rekayasa pengetahuan dimana dalam pembuatan rekayasa perangkat lunak ini, data yang terkumpul direpresentasikan sebagai basis pengetahuan keputusan, basis aturan dan perancangan mesin inferensi, selanjutnya perancangan sistem, yang merancang pembuatan pemodelan proses yang terdiri usecase dan activity diagram, pemodelan data yang terdiri dari perancangan table, pengembangan proses selanjutnya adalah implementasi menggunakan berbasis website. Hasil penelitian berupa program aplikasi sistem pakar yang mampu mendiagnosa penyakit Campak. Keluaran sistem berupa hasil diagnosis meliputi tentang penyebab penyakit, penularan penyakit, pencegahan penyakit dan solusi penyakit campak pada anak. Dan juga dilengkapai dengan MB, MD dan nilai C.F yang diperoleh dengan perhitungan menggunakan metode Certainty Faktor.Kata Kunci— Diagnosa, Campak, Rubella, Certainty FactorMeasles is a contagious disease that is still a health problem in Indonesia , as often reported in some areas . According to data SKR (1996 ) the incidence of measles in infants at 582/10.000. The method used is the Certainty Factor method or methods Kepastian.Tujuan this research is to create a software expert system that is expected to assist the community in diagnosing type measles expert system software include user needs analysis, requirements analysis and system design engineering knowledge which in pmbuatan this software engineering, data collected represented as a knowledge base, decision, rule base and inference engine design, system design further, the design creation process use case and activity diagram, data modeling which consists of designing Table Mapping, designing go round the table next process inplementasi development using website based. The results in the form of an expert system application program that is able to diagnose diseases such as measles output system disease diagnosis include the value of MB and CF values obtained by calculation using the method of Certainty factors, causes and solutions.Keywords—Diagnosis, Measles, Rubella, Certainty Factor

scholarly journals Perancangan Sistem Pakar Untuk Mendiagnosa Penyakit Diabetes Mellitus Menggunakan Metode Certainty Factor Design Expert System for Diagnosing Diabetes Mellitus Using Certainty Factor Method

CCIT Journal ◽  
2018 ◽  
Vol 11 (2) ◽  
pp. 182-191
Author(s):  
Musthofa Galih Pradana ◽  
Bondan Wahyu Pamekas ◽  
Kusrini Kusrini
Keyword(s):  
Diabetes Mellitus ◽  
Expert System ◽  
System Design ◽  
Design Process ◽  
Interface Design ◽  
Medical Personnel ◽  
The Body ◽  
Design System ◽  
Certainty Factor ◽  
Prevention Of Diabetes

Diabetes mellitus is a chronic metabolic disorder caused by the pancreas that does not produce enough insulin, so the body works to be disturbed. But by knowing the symptoms that exist, prevention of diabetes mellitus disease can be done as early as possible with the help of expert systems.One method of expert system used to diagnose symptoms of Diabetes Mellitus is Certainty Factor. The process undertaken in this research starts from literature studies, system design, system implementation and the last is testing the system. In the system design process is done by designing the database required by the expert system and also design the system interface design. After the design process is done then the next step is to implement the design into an expert system application. By using this method, the system gives results of possible symptoms experienced, presentation of beliefs, and treatment solutions based on the facts and the value of confidence given by users in filling out questions that have been given by the system.The results of this system are used to help medical personnel and patients in order to identify the symptoms of diabetes mellitus

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 Android-based expert system design for drug selection using certainty factor

2019 ◽  
Vol 1280 ◽  
pp. 022018
Author(s):  
C Slamet ◽  
B Firmanda ◽  
M A Ramdhani ◽  
W Darmalaksana ◽  
E Enjang ◽  
...  
Keyword(s):  
Expert System ◽  
System Design ◽  
Drug Selection ◽  
Certainty Factor

The Study of Hybrid Gaussian CBR Technique and Using in Camshaft Design System

2010 ◽  
Vol 108-111 ◽  
pp. 603-607
Author(s):  
Wei Yan ◽  
Xue Qing Li ◽  
Xu Guang Tan ◽  
De Hui Tong ◽  
Qi Gao
Keyword(s):  
Expert System ◽  
Decision Model ◽  
Nearest Neighbor ◽  
Design System ◽  
Case Based Reasoning ◽  
K Nearest Neighbor ◽  
Engine Design ◽  
Cam Profile ◽  
Aided Design ◽  
Case Based

In this paper, we propose a hybrid decision model using case-based reasoning augmented the Gaussian and k nearest neighbor methods for aided design camshaft in engine. The hybrid Gaussian k-NN (HGKNN) CBR scheme is designed to compute memberships between cam profile and engine parameters, which provides a more flexible and practical mechanism for reusing the decision knowledge. These methods were implemented in the database application and expert system following the examples of Cam Profile. To get the designed case, the retrieved results were compared and analyzed by HGKNN and k-NN algorithm in the CBR database. It proves the validity of HGKNN and CBR design system is used successfully in engine design process.

scholarly journals Expert System for Simulation of Pest and Disease Diagnosis in Onion Plant Using Putty Shafer Method and Rule-Based Approach

2019 ◽  
Vol 2 (1) ◽  
pp. 1-8
Author(s):  
Melia Dianingrum ◽  
Nandang Hermanto ◽  
Mohamad Iqbal Rifa'i
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Well Testing ◽  
Application Development ◽  
Onion Plant ◽  
Pests And Diseases ◽  
Output System ◽  
Last Stage ◽  
Development Evaluation ◽  
Rule Based Approach

The expert system is trying to adopt a system of human knowledge into a computer so that the computer can solve problems like the experts. The expert system is well designed in order to solve a particular problem by mimicking the work of the expert. The development of an expert system is expected to be resolved problems with the help of experts. The problems addressed by an expert not only the problems that rely on algorithms but sometimes elusive problems. An expert with knowledge and experience can overcome these problems. The application of an expert system in this study is made to diagnose pests and diseases in onion plants based on the web. The Data Collection method used is literature studies, interviews and observation. The stages of research used are literature review, data processing analyst, and Onion analyzed and photographed which then is uploaded and analyzed, Dempster Shafer method, application development, evaluation. In the last stage is the pilot study conducted using a Blackbox method and testing to the user. The result of the research is in the form of an expert system application that can diagnose pests and diseases of onion as many as 7 types of diseases. The output system is in the form of onion disease searching result obtained based on the symptoms inputted by the user. The result of Blackbox Testing is all functions of the application successfully run well. Testing to the users rated well both appearance and information of the application.

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.

PERANCANGAN SISTEM INFORMASI AKADEMIK JURUSAN ELEKTORNIKA

2019 ◽  
Vol 7 (2) ◽  
pp. 86
Author(s):  
Rizki Hardian Sakti ◽  
Elfi Tasrif
Keyword(s):  
Information Technology ◽  
Information System ◽  
Life Cycle ◽  
System Design ◽  
System Development ◽  
Flow Diagram ◽  
Design System ◽  
Activity Diagram ◽  
Development Life Cycle ◽  
Effective Manner

In this modern era today, information technology had become a thing where the society have to be cultivated. The development of information technology was currently running very fast and played an important role in various ways. Computers were one of the important parts in improving information technology. This research aimed to design a tool to be able to assist students in obtaining information in an accurate and effective manner. The design of this information system used the System Development Life Cycle (SDLC) method which was a common methodology in system development and design. System Development Life Cycle (SDLC) had six phases, are namely: identification, initiation and project design, analysis, design, implementation and maintenance. The design carried out were the design and normalization of the database, Entity Relations Diagram (ERD), and system design. The system design had Data Flow Diagram (DFD), Use Case Diagram, Activity Diagram, Sequence Diagram and Class Diagram.Keywords: Information System, System Development Life Cycle, Electonic

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

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