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Erwin Panggabean - One of the best experts on this subject based on the ideXlab platform.

  • Diagnose Disease Expert System Respiratory Tract Infection Method Using Certainty Factor
    2020
    Co-Authors: Aritana Lahagu, Erwin Panggabean
    Abstract:

    Respiratory tract infections are infectious diseases that interfere with the process of human breathing. When the breathing process takes place, there are often various kinds of diseases, most of which can only be treated by a lung specialist. The arrival of a pulmonary specialist for consultation can take hours and is expensive. Then we need an expert system that can quickly find out the type of disease in human breathing and how to handle it and the solutions that will be provided. Expert system is a system that uses human knowledge to find out the system that is entered into a computer and then is used to solve problems that usually require expertise or human expertise. One application of an expert system to diagnose respiratory tract infections is to use the Certainty Factor method. The Certainty Factor method is a method used to solve problems from uncertain answers, and also produce uncertain answers. This unCertainty is influenced by two Factors, namely uncertain rules and uncertain user answers. The research aims to build an expert system application for handling respiratory tract infection problems with Visual Studio 2010 as a tool for designing applications and using Microsoft Access 2007 Database as a database. This expert system is able to calculate similarity in weight calculation based on symptoms of respiratory tract infection using Certainty Factor methods and provide reports using crystal reports

  • Diagnose Disease Expert System Respiratory Tract Infection Method Using Certainty Factor: Diagnose Disease Expert System Respiratory Tract Infection Method Using Certainty Factor
    Journal Of Computer Networks Architecture and High Performance Computing, 2020
    Co-Authors: Aritana Lahagu, Erwin Panggabean
    Abstract:

    Respiratory tract infections are infectious diseases that interfere with the process of human breathing. When the breathing process takes place, there are often various kinds of diseases, most of which can only be treated by a lung specialist. The arrival of a pulmonary specialist for consultation can take hours and is expensive. Then we need an expert system that can quickly find out the type of disease in human breathing and how to handle it and the solutions that will be provided. Expert system is a system that uses human knowledge to find out the system that is entered into a computer and then is used to solve problems that usually require expertise or human expertise. One application of an expert system to diagnose respiratory tract infections is to use the Certainty Factor method. The Certainty Factor method is a method used to solve problems from uncertain answers, and also produce uncertain answers. This unCertainty is influenced by two Factors, namely uncertain rules and uncertain user answers. The research aims to build an expert system application for handling respiratory tract infection problems with Visual Studio 2010 as a tool for designing applications and using Microsoft Access 2007 Database as a database. This expert system is able to calculate similarity in weight calculation based on symptoms of respiratory tract infection using Certainty Factor methods and provide reports using crystal reports

  • analisis perbandingan metode dempster shafer dengan metode Certainty Factor untuk mendiagnosa penyakit stroke
    Journal Of Informatic Pelita Nusantara, 2018
    Co-Authors: Ira Lina Kendayto Panjaitan, Erwin Panggabean, Sulindawaty Sulindawaty
    Abstract:

    Stroke is one of the function of acute neurologic dysfunction caused by vascular disorders and occurs suddenly, if it continues and is not treated promptly can result in total paralysis and even death.Often difficult to obtain services and information because there is no expert stroke disease that can provide information on how to choose the right action for himself or a family member who is suffering from stroke is a problem that is often a constraint in the prevention of disease stroke is more developed. In this study the authors analyze the comparison of diagnosis result of Expert System of stroke by using the method of Dempster Shafer and Certainty Factor. In expert System application in one disease there are a number of evidences that will be used in unCertainty Factor in decision makin for diagnosis of a disease.To address some of these evedences on the theory of Dempster Shafer uses a rule better known as Dempster’s Rules of Combination. Certainty Factor is a theory to accommodate the inexact reasoning of an expert proposed by Shortliffe and Bhucanan in 1975. This expert system program is based on a website using the PHP programing language and MySQL database.  Keyword : Expert System, Dempster Shafer, Certainty Factor, PHP

Abdul Fadlil - One of the best experts on this subject based on the ideXlab platform.

  • Comparative Analysis of Certainty Factor Method and Bayes Probability Method on ENT Disease Expert System
    Scientific Journal of Informatics, 2018
    Co-Authors: Khairina Eka Setyaputri, Abdul Fadlil, Sunardi Sunardi
    Abstract:

    Expert system is computer programs that mimic the thought process and expert knowledge in solving a particular problem. Basically, an expert system has various methods to diagnose various kinds of diseases experienced by humans, animals, and plants. This research analyzes the comparison of Certainty Factor method and Bayes Probability method in the expert system of Ear, Nose, and Throat (ENT) diseases. Both methods have the same basic theory of overcoming uncertainties with existing variables. The Certainty Factor method has many variables that are used as systematic knowledge, namely the weight value of the expert which is the basis of knowledge of the system and the user input weight value, while the Bayes Probability method uses only expert knowledge in the calculation. Based on a comparative analysis of the methods obtained with 10 patients data on the ENT disease expert system, the Certainty Factor method has accuracy in diagnosing the disease by 100%, while the Probability Bayes method of system accuracy is 80%. So it can be concluded that the Certainty Factor method is more accurate in diagnosing ENT than the Bayes Probability method.

  • analisis metode Certainty Factor pada sistem pakar diagnosa penyakit tht
    Jurnal Teknik Elektro, 2018
    Co-Authors: Khairina Eka Setyaputri, Abdul Fadlil, Sunardi Sunardi
    Abstract:

    There are two Factors that cause a disease, called  Congenital and Acquired. Congenital refers to a disease a person is born with, while Acquired refers to a disease acquired after a person was born such as infection, trauma, and neoplasm. The infected person will sometimes require information on the disease before going to the doctor or a hospital. Such information may be found from a system which receives input on the symptoms and gives a clear information on the corresponding disease. This may be achieved via a system of experts, in which the expert refers to an ENT (Ear, Nose, and Throat) specialist. Such information is hoped to provide a solution on the disease. The system of ENT specialists designed and research in this paper used the Certainty Factor method. The method will overcome the unCertainty in decision making depending on the symptoms described by the user. This paper is successfully applied Certainty Factor method used as an instrument of decision making in the system of ENT specialists. The system is web-based, enabling the user to access and choose the symptoms of the disease as well as acquiring information on ENT diseases  easly.

  • sistem pakar mendiagnosa jenis penyakit stroke menggunakan metode Certainty Factor
    JSTIE (Jurnal Sarjana Teknik Informatika) (E-Journal), 2013
    Co-Authors: Poni Wijayanti, Abdul Fadlil
    Abstract:

    Penyakit  Stroke adalah serangan otak yang timbul secara mendadak dimana terjadi gangguan fungsi otak sebagian atau menyeluruh sebagai akibat dari gangguan aliran darah oleh karena sumbatan atau pecahnya pembuluh darah tertentu di otak, sehingga menyebabkan sel-sel otak kekurangan darah, oksigen atau zat-zat makanan dan akhirnya dapat terjadi kematian sel-sel tersebut dalam waktu relatif singkat. Gaya hidup yang dimaksud yaitu perubahan pola makan yang tadinya mengonsumsi menu rumahan yang tradisional menjadi mengkonsumsi junk food atau makanan cepat saji yang serba cepat, kaya lemak, dan enak. Serta perubahan pola hidup yang tadinya santai dan tenang menjadi serba tergesa-gesa, tidak sempat sarapan bahkan makan siang, tidak sempat bersosialisasi dan berolahraga. Metode yang digunakan adalah metode Certainty Factor (CF) atau nilai kepastian suatu penyakit. Tujuan penelitian ini adalah membuat perangkat lunak sistem pakar yang diharapkan dapat membantu masyarakat dalam mendiagnosis jenis penyakit stroke. Pengembangan perangkat lunak sistem pakar ini meliputi, analisis kebutuhan perangkat lunak yang terdiri dari 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 dari konteks diagram dan Data Flow Diagram (DFD), pemodelan data yang terdiri dari perancangan Entity Relationship Diagram (ERD), Mapping Table dan perancangan tabel. Pengembangan proses selanjutnya adalah implementasi menggunakan Visual Basic 6.0 dan tahap akhir pengembangan sistem yaitu pengujian dengan Black Box Test dan Alfa Test. Hasil penelitian berupa program aplikasi sistem pakar yang mampu  mendiagnosa sebanyak 6 Penyakit Stroke . Keluaran sistem berupa hasil diagnosa penyakit yang dilengkapi nilai MB, nilai MD dan nilai CF yang diperoleh dengan perhitungan menggunakan metode Certainty Factor, penyebab dan solusi. Kata kunci :  Jenis Penyakit Stroke, Sistem Pakar, Certainty Factor

Putu Manik Prihatini - One of the best experts on this subject based on the ideXlab platform.

  • Fuzzy Expert System for Tropical Infectious Disease Diagnosis by Certainty Factor
    TELKOMNIKA (Telecommunication Computing Electronics and Control), 2012
    Co-Authors: I Ketut Gede Darma Putra, Putu Manik Prihatini
    Abstract:

    Communication between doctor and patient play an important role in determining the diagnosis of the illness suffered by the patient. Consultation time constraints led to insufficient information obtained to produce a diagnosis. This limitation is overcome by developing an expert system using fuzzy logic to represent the vagueness of symptoms experienced by patients and the Certainty Factor represents a relationship between the symptoms and disease. Knowledge acquisition generate a knowledge base include the fact and rules with Certainty Factor value of the expert. Implication, composition and defuzzification are used in the process of fuzzy reasoning, and the results are combining with Certainty Factor. Web-based expert system is equipped with workplace, explanation facility and knowledge improvement. The results of expert diagnosis and web-based expert system diagnosis show the system, has similarity with the expert at 93.99%.

  • Fuzzy Expert System for Tropical Infectious Disease by Certainty Factor
    TELKOMNIKA (Telecommunication Computing Electronics and Control), 2012
    Co-Authors: I Ketut Gede Darma Putra, Putu Manik Prihatini
    Abstract:

    Communication between doctor and patient play an important role in determining the diagnosis of the illness suffered by the patient. Consultation time constraints led to insufficient information obtained to produce a diagnosis. This limitation is overcome by developing an expert system using fuzzy logic to represent the vagueness of symptoms experienced by patients and the Certainty Factor represents a relationship between the symptoms and disease. Fuzzy logic method begins with the acquisition of knowledge to produce the facts and rules, implication process, composition and defuzzification. The result of defuzzification used in the calculation of sequential and combined Certainty Factor which represent the belief percentage of diseases diagnosis that suffered by the patient. The results of the expert diagnosis with expert system for the given cases indicates the system, has the similarity diagnosis with the expert at 93.99%

Erwin Sutomo - One of the best experts on this subject based on the ideXlab platform.

  • Sistem Pakar Untuk Menentukan Penyakit Kucing Menggunakan Metode Certainty Factor
    2015
    Co-Authors: Dedy Tri Saputro, Jusak Jusak, Erwin Sutomo
    Abstract:

    Abstract: Contagious cat disease is one type of disease that is often infecting cats. Contagious diseases are part of the disease that spread from saliva, feces, urine, cakaran, aerosols, and also indirectly to other cats and keepers. An infectious disease is caused by several Factors, namely protozoa, viruses, bacteria and fungi, the effects of nutrients and the environment. In the absence of quickly and precise treatment, it will to lead to the transmission of the disease to other cats and people, worsely it can cause death cats. Based on the problems above, in this study, we develope an expert system that is able to assists in determining the cat diseases. Currently, there has not been any application for the dealing with identification of the diseases of cats. This expert system utilizes the Certainty Factor to determine any symptoms experienced by cats. The system will equalize with the existing rules. The system will provide decision of the cat's illness. Based on the experiment, it is evident that the expert system is able to determine cat diseases with accuracy of 93,3%. The results were obtained from testing of 15 tested cases done by vets. Keywords : Feline Diseases , Certainty Factor, Expert System

  • Sistem Pakar Diagnosis Penyakit Pada Ayam Petelur Menggunakan Metode Certainty Factor
    2014
    Co-Authors: Rohmat Solikin, Jusak Jusak, Erwin Sutomo
    Abstract:

    Chicken diseases often fear chicken farmers. In many cases, chicken diseases can reduce egg productivity of chickens. If there is one chicken affected and it doesn’t handle quickly and precisely, it indirectly can cause the other chickens affected as well that could potentially lead to death. On the other hand, there are limitation number of chicken veterinary in rural areas. Hence, the affected chickens cannot be handled as soon as possible. In this paper, we build an expert system with Certainty Factor method that is able to diagnose the chicken diseases computationally. Testing results shows that the expert system can identify chicken diseases with accuracy of 92,8%. The results were obtained by testing through 14 chickens that bear chicken diseases. Keywords: Expert System, Certainty Factor, Disease chicken

Paska Marto Hasugian - One of the best experts on this subject based on the ideXlab platform.

  • Tuberculosis Disease Diagnosis Expert System Method of Certainty Factor: Tuberculosis Disease Diagnosis Expert System Method of Certainty Factor
    Journal Of Computer Networks Architecture and High Performance Computing, 2020
    Co-Authors: Betti Mastaria Br Sembiring, Paska Marto Hasugian
    Abstract:

    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.

  • Implementation of Certainty Factor Method for Expert System
    Journal of Physics: Conference Series, 2019
    Co-Authors: Ade Setiawan Sembiring, Paska Marto Hasugian, Fristi Riandari, Sulindawaty, Olven Manahan, Merlin Helentina Napitupulu, R. Mahdalena Simanjorang, Agustina Simangunsong, Yulia Utami, Hengki Tamando Sihotang
    Abstract:

    PC computer is a flexible electronic device and can receive and process data quickly and accurately, and can also store data for a long time. There is a time when the PC hardware is damaged. So that it annoys the user. In connection with the problems that occur, the researchers aim to build an Expert System application to diagnose damage to PC computers using the Certainty Factor method by using Visual Studio 2010 applications and using Microsoft Access 2013 as a database. Applications that are built can be an alternative in knowing the type of damage and provide alternative solutions in handling damage to PC computer hardware.