scholarly journals INTESTINE DISEASE DIAGNOSIS SYSTEM USING CERTAINTY FACTOR METHOD

2019 ◽  
Vol 6 (1) ◽  
pp. 82-94
Author(s):  
Chandra - Kirana ◽  
Harrizki Arie Pradana ◽  
Rahmat - Sulaiman

Inside the human body there are many important organs, one of which is the intestine. Intestinal disease / digestive disease is a disease that most often attacks the digestive tract in humans. There are several intestinal diseases that are dangerous and there are also harmless intestinal diseases. In this research, researchers created an android-based expert system application that can provide information to the users about diseases that are being suffered through the symptoms experienced by the user. The process of making expert system applications using the certainty factor algorithm. The certainty factor algorithm is used to accommodate the uncertainty of an expert's. The mechanism that be used in the certainty factor algorithm on each symptom uses a measure of increased belief (MB) and measure of increased disbelief (MD). Expert system applications that have been built to detect intestinal diseases based on Android have been successfully implemented with a presentation of accuracy of 99.7265625%. by that percentage, it show us that the diagnosis of symptoms of the selected disease is in suitable by the experienced of user, and has the accuracy determined by the system

2019 ◽  
Vol 5 (3) ◽  
pp. 185
Author(s):  
Muqorobin Muqorobin ◽  
Prabowo Budi Utomo ◽  
Muhammad Nafi’Uddin ◽  
Kusrini Kusrini

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


Author(s):  
Bagus Fery Yanto ◽  
Indah Werdiningsih ◽  
Endah Purwanti

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


Author(s):  
Nandra Sunaryo ◽  
Yuhandri Yunus ◽  
S Sumijan

Identification of the development of special interests and talents needs to be done in order to find out the potential of students. This knowledge is needed by the teacher when providing counseling guidance to students in order to know the types of special interests and talents of students. This study aims to identify the development of special interests and talents in students based on the characteristics of special interests and talents appropriately. In this study using the Certainty Factor method where this expert system can assist experts in identifying the development of special interests and talents based on the characteristics of special interests and talents in students. Followed by calculating the level of accuracy with the results of the counseling guidance teacher analysis. The results of the testing of the Certainty Factor method were successfully applied by comparing the data with the system that had been designed so that a good level of accuracy was obtained from the results of the system calculations with expert decisions of 80% of the 5 test data. This expert system application can be used as an alternative in identifying the development of special interests and talents in students.


2021 ◽  
Vol 6 (2) ◽  
pp. 96
Author(s):  
I Wayan Rangga Pinastawa ◽  
Ema Utami ◽  
M. Rudyanto Arief

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


2021 ◽  
Vol 5 (1) ◽  
pp. 74
Author(s):  
Syavira Cahyaningsih ◽  
Agung Triayudi ◽  
Ira Diana Sholihati

Using skincare and facial skin care must be in accordance with the type of facial skin, because if it is not suitable, it can cause problems such as facial skin breakouts, dry skin, irritated skin, and acne prone skin. To find out the type of facial skin, you have to do an examination with a skin and genital specialist, but the high cost of consultation and the long queue process is an obstacle for everyone. Therefore, the authors created an expert system to identify facial skin types using a combination of certainty factor methods with forward chaining techniques. The diagnostic results from calculations using an expert system application and the results of manual calculations from one of the respondent data from 100 respondent data, namely producing the same level of confidence, each of which produces a percentage of 99.45% and the diagnostic results state that the user has a normal skin type.


Author(s):  
Kurniawan Jefdy ◽  
Sarjon Defit ◽  
Yuhandri Yunus

Developing an expert system application in providing an overview of the interests of students to help decision making interests in the vocational field so that they are right on target in choosing a major. In this study, using the Certainty Factor method and the Fordward Chaining method where this expert system can help experts identify vocational interests based on the characteristics of vocational interest in students. The personality types used to determine the type of vocational interest are Tangible, Thinking, Flexible, and Entrepreneur. The results of system calculations with expert decisions are worth 80% of the 4 test data, so a good level of accuracy is obtained. The resulting expert system can help students quickly provide an overview of vocational interest in making department decisions in continuing higher education, can carry out online consultations, document files, and can be used as a consultation portal for students.


Author(s):  
Betti Mastaria Br Sembiring ◽  
Paska Marto Hasugian

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.


2020 ◽  
Vol 1 (2) ◽  
pp. 26
Author(s):  
Rosyid Ridlo Al Hakim ◽  
Erfan Rusdi ◽  
Muhammad Akbar Setiawan

Since being confirmed by WHO, the status of COVID-19 outbreak has become a global pandemic, the number of cases has been confirmed positive, cured, and even death worldwide. Artificial intelligence in the medical has given rise to expert systems that can replace the role of experts (doctors). Tools to detect someone affected by COVID-19 have not been widely applied in all regions. Banyumas Regency, Indonesia is included confirmed region of COVID-19 cases, and it’s difficult for someone to know the symptoms that are felt whether these symptoms include indications of someone ODP, PDP, positive, or negative COVID-19, and still at least a referral hospital handling COVID-19. Expert system with certainty factor can help someone make a self-diagnose whether including ODP, PDP, positive, or negative COVID-19. This expert system provides ODP diagnostic results with a confidence level of 99.96%, PDP 99.99790%, positive 99.9999997%, negative 99.760384%, and the application runs well on Android OS


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