scholarly journals Sistem Pakar Diagnosa Penyakit THT Menggunakan Metode Dempster Shafer

Repositor ◽  
2020 ◽  
Vol 2 (9) ◽  
Author(s):  
Doni Yulianto ◽  
Yufiz Azhar ◽  
Nur Hayatin
Keyword(s):  
Expert System ◽  
Search Method ◽  
Rule Based ◽  
Forward Chaining ◽  
Lack Of Information ◽  
The Subject ◽  
The Right ◽  
Uncertainty Method ◽  
Development Step ◽  
Nose And Throat

AbstrakBerbagai penyakit pada manusia dapat menimbulkan masalah serius jika tidak cepat ditangani, seperti halnya penyakit THT (Telinga, Hidung, dan Tenggorokan). Penderita penyakit THT di Indonesia cukup tinggi, karena masyarakat sering menganggap remeh penyakit THT dan kurangnya informasi mengenai penyakit tersebut. Perlu adanya sistem yang memberikan informasi mengenai gejala pada penyakit THT dan jenis penyakit apa saja yang diderita, serta solusi apa yang tepat untuk menangani penyakit THT. Subjek dalam penelitian ini adalah sistem pakar untuk mendiagnosa penyakit THT. Pada penelitian ini menggunakan dua metode, yaitu metode ketidakpastian menggunakan Dempster Shafer dan metode penelusuran yaitu Forward Chaining. Langkah pengembangan diawali dari pengumpulan data, lalu pembuatan Rule Based, mengimplementasikan metode, dan melakukan pengujian akurasi pakar. Hasil penelitan ini adalah sistem pakar mendiagnosa penyakit THT sebanyak 7 jenis penyakit dengan gejala sebanyak 24 jenis. Penelitian ini juga menggunakan metode Dempster Shafer untuk mendapatkan nilai kepastian berupa persentase nilai kepastian pada hasil diagnosa penyakitnya. Berdasarkan hasil pengujian pakar, dapat disimpulkan bahwa sistem pakar memiliki tingkat kesamaan dengan pakar sebesar 85% yang berarti bahwa sistem pakar ini layak untuk digunakan.AbstractVarious diseases in humans can cause serious problems if not quickly handled, such as ENT diseases (ear, nose, and throat). People with ENT disease in Indonesia is quite high, because people often consider the condition of ENT disease and lack of information about the disease. There is a system that provides information about the symptoms in ENT diseases and what types of diseases suffered, as well as what is the right solution to handle ENT diseases. The subject in this study is an expert system for diagnosing ENT diseases. The study used two methods, namely the uncertainty method using Putty Shafer and the search method that is Forward Chaining. The development step starts from collecting data, then creating a Rule Based, implementing methods, and conducting expert accuracy testing. The results of this research is a system of experts diagnose ENT diseases as many as 7 types of diseases with the symptoms as much as 24 types. This research also uses the method of putty Shafer to get certainty of the percentage value of certainty in the diagnosis of diseases. Based on expert testing results, it can be concluded that an expert system has a level of similarity with experts at 85% which means that the expert system is worthy of use.

scholarly journals PENGEMBANGAN SISTEM PAKAR PEMILIHAN JAMU DENGAN DIAGNOSA PENYAKIT PADA MANUSIA DENGAN METODE FORWARD CHAINING

2021 ◽  
Vol 9 (01) ◽  
pp. 11-18
Author(s):  
Teguh Pradana ◽  
Moch. Zul Ilmi ◽  
Teguh Arifianto
Keyword(s):  
Clinical Trials ◽  
Expert System ◽  
Herbal Medicine ◽  
Herbal Products ◽  
Forward Chaining ◽  
The Right

Herbal medicine is a medicine from natural ingredients whose properties have not been scientifically proven, in other words, it has not been subjected to clinical or clinical trials, but its properties are trusted by people based on experience. And at this time many herbal products are marketed in general, and not a few people are confused to choose the right herbal medicine according to their circumstances, so people have to consult or ask before choosing, and make the store experience a long queue on customers. Therefore an expert system is needed for herbal medicine so that people can choose the right herbal medicine according to their circumstances or conditions, and this system can reduce the queue at the herbal medicine shop customers. Expert system built in this study uses the forward chaining method. Case study for the system that is "Pasuruan herbal shop fan" which contained 70 types of herbal medicine, the results of tests conducted by this system are in accordance with the diagnosis.

scholarly journals Penalaran Berbasis Aturan Untuk Diagnosa Awal Penyakit Anjing Menggunakan Teorema Bayes

2018 ◽  
Vol 2 (2) ◽  
pp. 530-535 ◽  
Author(s):  
Sella Marselena ◽  
Ause Labellapansa ◽  
Abdul Syukur
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Rural Areas ◽  
Medical Personnel ◽  
Bayes Theorem ◽  
Search Method ◽  
Early Symptoms ◽  
Forward Chaining

Many pets can be played with, socialize and even live together with humans. Numbers of animal clinics have increased to provide care for pets. This study focuses on Dog as pet. Desease and improper treatment of dog will adversely affect the Dog. In dealing with the problem of Dog disease, Dog owners may experience difficulties due to limited number of clinics and veterinarians, especially in rural areas. As a solution, Artificial Intelligence is used by using expert systems that can help inexperienced medical personnel diagnose early symptoms of Dog disease. The search method used in this research is Forward Chaining and Bayes Theorem method to handle uncertainties that arised. Based on knowledge acquisition, 3 diseases were obtained with 38 simptoms and 60 cases. Based on the tests conducted then obtained the sensitivity value of 80%, the value of accuracy of 88.6% indicates that this expert system is able to diagnose dog diseasesKeywords: Dog, Expert System, Forward Chaining, Bayes Theorem.  

scholarly journals Sistem Pakar Juru Pemantau Jiwa (Jumanji) Berbasis Web Dengan Metode Forward Chaining

2020 ◽  
Vol 1 (1) ◽  
pp. 23-34
Author(s):  
Muhammad Adil ◽  
Henny Leidiyana
Keyword(s):  
Expert System ◽  
Mental Disorders ◽  
Black Box ◽  
Web Based ◽  
The Public ◽  
Forward Chaining ◽  
Lack Of Information ◽  
The Family ◽  
Box Method ◽  
Made In

Abstract   Through the mass media news is often found about how a family or community handles family members who have mental disorders by mounting, isolating, and even throwing them away. This shows that one of the things that causes the family to handle the problem inappropriately is the lack of information about diagnoses of mental disorders so that they take actions that could make the sufferer worse. The expert system designed by the writer here aims to produce an expert system that can be used by the general public. The system is made in such a way that it can be used easily to provide knowledge to the public about mental disorders and how to deal with it. With this expert system, families and even the surrounding community can take appropriate action if there are people with mental disorders in the vicinity. This expert system uses a method that is quite popular, namely Forward Chaining which is implemented in the form of a web-based application program. Application is made using the PHP programming language then testing based on the Black Box method   Keywords: Expert system, Mental disorder, Forward Chaining.   Abstrak   Melalui media massa sering dijumpai berita tentang bagaimana sebuah keluarga atau masyarakat menangani anggota keluarganya yang mengalami gangguan jiwa dengan cara memasung, mengucilkan, bahkan membuangnya. Ini menunjukkan bahwa salah satu hal yang menyebabkan keluarga kurang tepat dalam menangani permasalahan tersebut adalah kurangnya informasi tentang diagnosa gangguan jiwa sehingga mereka melakukan tindakan yang bisa jadi membuat penderita semakin parah. Sistem pakar yang dirancang penulis di sini bertujuan untuk menghasilkan sistem pakar yang dapat digunakan oleh masyarakat secara umum. Sistem yang dibuat sedemikian rupa sehingga dapat digunakan secara mudah untuk memberikan pengetahuan kepada masyarakat tentang gangguan jiwa dan cara menanganinya. Dengan adanya sistem pakar ini, keluarga bahkan masyarakat di sekitarnya dapat melakukan tindakan yang tepat jika ada penderita gangguan jiwa di sekitarnya. Sistem pakar juru pemantau jiwa ini menggunakan metode yang cukup populer yaitu forward Chaining yang diimplementasikan ke dalam bentuk program aplikasi berbasis web. Aplikasi dibuat menggunakan bahasa pemograman PHP kemudian dilakukan pengujian berdasarkan dengan metode Black Box.   Kata Kunci: Sistem pakar, gangguan jiwa, Forward Chaining.

scholarly journals Rancang Bangun Aplikasi Sistem Pakar Berbasis Android untuk Mendeteksi Kerusakan pada Air Conditioner (AC)

Jurnal INFORM ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Rinabi Tanamal
Keyword(s):  
Expert System ◽  
Air Conditioning ◽  
Air Conditioner ◽  
Android Application ◽  
Air Conditioners ◽  
Forward Chaining ◽  
Air Temperatures ◽  
Main Components ◽  
The Right ◽  
Electrical Components

Abstract— Air Conditioner (AC) is a system or machine designed to stabilize the air and air temperatures that cover a certain area. This study discusses how to find ways to improve Android-based system applications for air protection in Air Conditioning (AC), this method is used as a support in making decisions on damage to Air Conditioner (AC) on the main components, supporting components, electrical components and cooling materials (Refrigerant) in Air Conditioner (AC). To design the application, an expert system is needed. Expert system itself is a computer system that emulates the ability of human expertise (Sri Hartati and Sari Iswanti, 2008: 152). The purpose of this study is to be able to produce an expert system application that can help technicians to improve damage to the Air Conditioner (AC) so that users of Air Conditioning (AC) can also understand the damage that occurs in Air Conditioners (AC). The research inference method used in this expert system uses the Android-based Forward Chaining method. Forward Chaining is a strategy in finding data by collecting data or facts which will then be concluded to find the right solution or event to solve a problem. The shell expert system used is McGoo which will then be adopted into the Thunkable Android application. With the existence of this expert system aims to identify damage to the Air Conditioner (AC) and used as material in making decisions to help the users, especially the technicians in diagnosing the damage that is in the Air Conditioner (AC). The results of this study indicate that the existence of a hierarchy of decisions to detect damage to the Air Conditioner (AC) can be applied in the society and from the results of application testing it can be concluded that the application of this expert system will be a tool for users of Air Conditioners and technicians to diagnose damage to Air Conditioner (AC). 

scholarly journals APLIKASI SISTEM PAKAR DIAGNOSA PENYAKIT GIGI METODE FORWARD CHAINING DI UPTD KESEHATAN PUSKESMAS BANGIL

JOUTICA ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 205
Author(s):  
Kurniawan Wahyu Haryanto ◽  
Ari Dwi Cahyono
Keyword(s):  
Expert System ◽  
Computer Science ◽  
Health Center ◽  
Dental Health ◽  
Computer Software ◽  
Patient Data ◽  
Search Method ◽  
Dental Disease ◽  
Medical Field ◽  
Forward Chaining

Teeth are organs that are very important and very vital. Therefore dental health is very important. Most of the Indonesian people, the appeal for dental examinations every six months is more often considered a breeze then, because they are more concerned with the health of other organs. Though diseases that attack teeth can have a very significant effect such as appearance problems. This research applies computer science in the medical field, especially for dental disease problems at the UPTD Health Center in Bangil using the expert system concept. Expert system is a system in the form of computer software where the computer is made as if - will think like an expert or expert in the field. The search method used is forward chaining, which is a search where facts are known to support conclusions. This expert system makes it easy for patients to conduct consultations, making it easier for the admin to manage symptom data and their illnesses and patient data, judging from the results of the questionnaire which states that it is very useful, can be used as a temporary doctor.

scholarly journals Purwarupa Sistem Pakar dengan Mamdani Product untuk Menentukan Menu Harian Penderita DM

2013 ◽  
Vol 7 (1) ◽  
pp. 45
Author(s):  
Nur Hasanah ◽  
Retantyo Wardoyo
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Inference Engine ◽  
Rule Based ◽  
Knowledge Based ◽  
Menu Planning ◽  
Model Complex ◽  
Uncertainty Method ◽  
Management Expert ◽  
Diabetes Melitus

AbstrakPada 2025 diperkirakan 12,4 juta orang yang mengidap Diabetes Melitus (DM) di Indonesia. Perencanaan makan merupakan salah satu pilar dalam pengelolaan DM. Sistem pakar dapat berfungsi sebagai konsultan yang memberi saran kepada pengguna sekaligus sebagai asisten bagi pakar. Logika fuzzy fleksibel, memiliki kemampuan dalam proses penalaran secara bahasa dan memodelkan fungsi-fungsi matematika yang kompleks. Penelitian ini bertujuan menerapkan metode ketidakpastian logika fuzzy pada purwarupa sistem pakar untuk menentukan menu harian. Manfaat penelitian ini adalah untuk mengetahui keakuratan mesin inferensi Mamdani Product.            Pendekatan basis pengetahuan yang digunakan pada sistem pakar ini adalah dengan Rule-Based Reasoning. Proses inferensi pada sistem pakar menggunakan logika fuzzy dengan mesin inferensi Mamdani Product. Fuzzifier yang digunakan adalah Singleton sedangkan defuzzifier yang digunakan adalah Rata-Rata Terpusat. Penggunaan kombinasi Singleton fuzzifier, mesin inferensi Product dan defuzzifier Rata-Rata Terpusat yang digunakan pada sistem pakar dapat diterapkan untuk domain permasalahan yang dibahas. Meskipun demikian, terdapat kemungkinan Singleton fuzzifier tidak dapat memicu beberapa atau semua aturan. Jika semua aturan tidak dapat dipicu maka tidak dapat disimpulkan kebutuhan kalori hariannya. Kata kunci— sistem pakar, logika fuzzy, mamdani product, diabetes, menu  AbstractIt is predicted that 12.4 million people will suffer from Diabetes Mellitus (DM) in Indonesia in 2025. Menu planning is one of the important aspects in DM management. Expert system can be used as a consultant that gives suggestion to users as well as an assistant for experts. Fuzzy logic is flexible, has the ability in linguistic reasoning and can model complex mathemathical functions. This research aims to implement fuzzy logic uncertainty method into expert sistem prototype to determine diabetic daily menu. The advantage is to find out the accuracy of Mamdani Product inference engine. The knowledge-based approach in this expert system uses Rule-Based Reasoning. The inference process employs fuzzy logic making use of Mamdani Product inference engine. The fuzzifier used is Singleton while defuzzifier is Center Average.            The combination of Singleton fuzzifier, Mamdani Product inference engine and Center Average defuzzifier that is used can be applied in the domain of the problem under discussion. In spite of the case, there is possibility that Singleton fuzzifier can’t trigger some or all of the rules. If all of the rules can’t be triggered then the diabetic daily menu can’t be concluded. Keyword— expert system, fuzzy logic, mamdani product, diabetes, menu

scholarly journals Dog Disease Expert System Using Certainty Factor Method

SinkrOn ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 98
Author(s):  
Linda Marlinda ◽  
Widiyawati Widiyawati ◽  
Wahyu Indrarti ◽  
Reni Widiastuti
Keyword(s):  
Expert System ◽  
Herbal Medicines ◽  
Physical Symptoms ◽  
Certainty Factor ◽  
Factor Method ◽  
Lack Of Information ◽  
Loss Of Appetite ◽  
The Right ◽  
Final Question ◽  
Canine Diseases

Many animal keepers at home who do not know the disease contained in the animal's body. Especially for dogs, the lack of information begins to provide care, hygiene, vaccinations for the health of pet dogs and sickles that will be caused by dogs to their owners. Expert systems can provide solutions to the lack of information obtained by pet dog owners, especially dogs. With this expert system, the owner can know the dog's disease and realize the right prevention in treatment. In this paper 25, physical symptoms of the disease are used and found 8 types of common dog diseases. Five options are given to answer the calculation question using each method: no, quite sure, sure enough, certain, and certainty sure. Accuracy Analysis of each method is tested by assessing the results of each analysis method based on user feedback. The results of this study are the application of an expert system that can diagnose dogs using herbal medicines from plants. The purpose of this study is to implement the certainty factor method in the diagnosis system of canine diseases that can provide space in providing value confidence in knowledge. The conclusion in this study will show some questions as indicators of the characteristics of canine disease, until the final question. The conclusion of the study using the certainty factor method will show the characteristics of the disease in dogs. By being obtained from Rabies (0.9) with easy to get angry refuse nomal food; Hepatitis (0,9) with swelling of the liver occurs; Distemser (0,8) with stomach part blister and festering discharge from the eye; canine parvorius (0,8) with loss of appetite and poop there is blood, herpesvirus (0,8) with  often roared and complaints,  papilomatosis (0,9) with Smelly dog breath, and leptospirosis (0,7) with complaints, and dirofilaria immitis (0,9) with Unstable body temperature

scholarly journals Accuracy Level of Diagnosis of ENT Diseases in Expert System

KOMTEKINFO ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 127-134
Author(s):  
Dede Wira Trise Putra ◽  
Ade Oka Utami ◽  
Minarni ◽  
Ganda Yoga Swara
Keyword(s):  
Expert System ◽  
Early Detection ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Test Results ◽  
Forward Chaining ◽  
Accuracy Level ◽  
Nose And Throat ◽  
Delay In Treatment

Purpose of this study is to test the accuracy of ear, nose and throat (ENT) diseases with an expert system. The expert system is designed to help people make early detection of illnesses so that the possibility of delay in treatment can be minimized. The method used is Naive Bayes with Forward Chaining Inference for 14 types of diseases with 42 symptoms originating from ENT specialists. The method was tested on 25 patients who used an expert system and adjusted the results of expert diagnoses. The test results are influenced by the number of symptoms, so that the accuracy obtained is only 88%. So this research is needed to be further developed to find a more reliable expert system in diagnosing ENT diseases.

Sign in / Sign up

Export Citation Format

Share Document