Expert System To Detect Human’s Skin Diseases Using Forward Chaining Method Based On Web Mobile

Skin is a sense of touch in humans’ body which one of its functions is to feel the touch. Another function of the skin is to release the residual substances such as sweat. This part of the human body is very sensitive, easy to get hurt, and feels a sense of sensitivity. Human skin consists of epidermis and dermis. Skin diseases can be caused by a decrease in the immune system, allergies, viruses, or other causes. Skin disease is generally caused by a less guarded hygiene, bacteria, viral, allergic reactions, and low body resistance. If the cause of skin disease is only due to a lack of maintaining cleanliness, it can be prevented by changing lifestyles to be cleaner and healthier. Especially in Indonesia which is a tropical country, where the humidity is very high and can increase the development of bacteria on the skin. In another situation, not all people understand skin diseases for treatment or prevention. By the reason, The Forward Chaining Method is made to provide information about diagnoses of several skin diseases and produces conclusions. The existence of this expert system application makes it easy for people to get any information about skin diseases

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Akurasi dalam Mendeteksi Penyakit Kulit Menular menggunakan Gabungan Metode Forward Chaining dengan Certainty Factor

Jurnal Informasi & Teknologi ◽

10.37034/jidt.v2i2.58 ◽

2020 ◽

pp. 48-55

Author(s):

Deosa Putra Caniago ◽

Sumijan

Keyword(s):

Expert System ◽

Skin Disease ◽

Skin Diseases ◽

Medical Personnel ◽

Certainty Factor ◽

Natural Conditions ◽

Forward Chaining ◽

The Right ◽

Infectious Skin Diseases

The skin is the outer protective organ for humans. Skin is the most interacting layer with the environment. Interactions that occur are not always safe against bacteria, viruses, fungi and parasites, so they will cause harm. Poor interactions will result in skin diseases. This skin disease is often considered normal, but can be dangerous and deadly and contagious. Due to the natural conditions and lack of medical personnel, sufferers of skin diseases have problems in examining their skin diseases. So this research was conducted by using an Expert System (Expert System) to help sufferers of skin diseases and help get solutions to these diseases. The solution obtained from the symptoms felt by sufferers. The method used in this study is Forward Chaining (FC) and processed using the Certainty Factor (CF) Method. The results of this study can determine the right initial steps in dealing with infectious skin diseases. So this research is very helpful for sufferers in knowing the type of skin disease, the solution in its prevention and its prevention precisely.

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Pengembangan Sistem Pakar Berbasis Android untuk Menentukan Obat Generik pada Penyakit Kulit Menggunakan Metode Forward Chaining

INOVTEK Polbeng - Seri Informatika ◽

10.35314/isi.v6i1.1578 ◽

2021 ◽

Vol 6 (1) ◽

pp. 1

Author(s):

Rinanza Zulmy Alhamri ◽

Abidatul Izzah ◽

Kunti Eliyen

Keyword(s):

Expert System ◽

Skin Disease ◽

Skin Diseases ◽

Generic Drugs ◽

Disease Diagnosis ◽

Generic Medicine ◽

Design System ◽

Common Disease ◽

Forward Chaining ◽

Analysis System

Skin disease can be suffered by all people and ages as a common disease. In general treatment for people with skin diseases is by consulting to medical experts and asking for a medicine prescription. However, by utilizing current communication technology, sufferers are able to get good information about skin diseases. The expert system for the diagnosis of skin diseases has been done before. However, the expert system is built based on web and desktop, so it is less flexible in use, moreover in supporting self assistance for the skin disease sufferer. Therefore, this study aims to develop an Android-based expert system that can help diagnose skin diseases in humans as well as provide recommendations of generic medicine as first aid. The expert system developed by implementing the Forward Chaining (FC) method as an inference technique. This research was conducted in five phases, namely data collection, analysis system, design system, implementation, and testing. The knowledge base in this expert system includes 39 types of skin diseases, 83 symptoms, 16 types of generic drugs, 150 lines rules of skin disease diagnosis, and 39 lines recommendations of generic drug.

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DEMPSTER SHAFER'S ROLE IN THE EXPERT SYSTEM IN DIAGNOSING PET SKIN DISEASES

KLIK - KUMPULAN JURNAL ILMU KOMPUTER ◽

10.20527/klik.v6i1.216 ◽

2019 ◽

Vol 6 (1) ◽

pp. 107

Author(s):

Gita Malinda ◽

Andi Farmadi ◽

Muliadi Aziz

Keyword(s):

Expert System ◽

Skin Disease ◽

Skin Diseases ◽

Early Prevention ◽

Confidence Value

Cats are pets that are very close to humans. Infectious pet diseases can sometimes spread quickly and can be fatal, both in animals and humans. For early prevention, the pet disease must be immediately known which in this case is a cat skin disease. To find out the diagnosis of cat skin disease using the Dempster-Shafer method. So that the results obtained the strongest confidence value of cat skin disease {A1, A3, A4} which is equal to 0.48, which was obtained from three existing symptoms, namely wet dry crust, moist inner moist ear and frequent scratching.Keywords: Cats, Expert System, Dempster Shafer.Kucing merupakan hewan peliharaan yang sangat dekat dengan manusia.. Penyakit hewan peliharaan yang menular terkadang dapat menyebar secara cepat dan dapat berakibat fatal, baik pada hewan dan manusia. Untuk pencegahan dini maka penyakit hewan peliharaan tersebut harus segera diketahui yang dalam kasus ini adalah penyakit kulit kucing. Untuk mengetahui diagnose penyakit kulit kucing tersebut menggunakan metode dempster-shafer. Sehingga memproleh hasil Nilai keyakinan paling kuat terhadap penyakit kulit kucing {A1,A3,A4} yaitu sebesar 0,48, yang didapat dari tiga gejala yang ada yaitu kerak kering basah, bagian dalam telinga basah lembab dan sering menggaruk.Kata kunci: Kucing, Sistem Pakar, Dempster Shafer.

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Expert System for Diagnosing Human Skin Diseases Using Web-Based Naïve Bayes Method

Procedia of Engineering and Life Science ◽

10.21070/pels.v1i2.1021 ◽

2021 ◽

Vol 1 (2) ◽

Author(s):

Khoirunnisa devita Sari ◽

Ade Eviyanti

Keyword(s):

Expert System ◽

Human Skin ◽

Skin Disease ◽

Skin Diseases ◽

Naive Bayes ◽

Expert Knowledge ◽

Naïve Bayes ◽

Bayes Method ◽

Web Based ◽

Naive Bayes Method

Skin disease is a disease that often found in tropical countries like Indonesia. According to the survey, skin disease is the third of the ten most outpatient diseases. Lack of public knowledge about skin diseases and how to prevent and treat them can cause a person to develop acute skin diseases. The purpose of this research is to create an expert system application for diagnosis of human skin diseases using the web-based naïve Bayes method. With expert system, it hoped that human skin diseases can be detected early and can minimize the occurrence of more dangerous diseases. The calculation in this expert system uses the naïve Bayes method. This expert system makes diagnosis by analyzing input of symptoms experienced by patient and then processing it using certain rules according the expert knowledge that has been stored in the knowledge base. The result of this research is to build an expert system for diagnosing human skin diseases using website-based naïve Bayes. The results of the system trial of 20 respondents were the website could provide diagnosis results based on the inputted rules and could diagnose skin diseases properly. This website can used as an alternative use of technology so it can be used to diagnose skin diseases quickly, precisely and accurately. So in the future the handling of skin diseases can be faster and more efficient.

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DIAGNOSA PENYAKIT PADA KAMBING DENGAN SISTEM PAKAR BERBASIS ANDROID

Respati ◽

10.35842/jtir.v13i2.227 ◽

2018 ◽

Vol 13 (2) ◽

Author(s):

Muhammad Rizki Setyawan ◽

Andika Agus Slameto

Keyword(s):

Decision Making ◽

Expert System ◽

Rural Areas ◽

Search Technique ◽

Early Disease ◽

Forward Chaining ◽

Very High

INTISARIPengetahuan yang kurang akan penyakit pada kambing ditengah masyarakat dalam upaya identifikasi awal penyakit mempengaruhi pengambilan keputusan secara mandiri. Ketergantungan terhadap pengetahuan seorang pakar atau dokter hewan sangatlah tinggi, tetapi keberadaannya tidak selalu ada dan sangat susah ditemui, terutama di daerah pedesaan. Ditambah dengan masalah biaya dan sangat tidak efisien dari segi waktu.Oleh karena itu dalam penelitian ini dirancang sebuah sistem pakar dengan metode forward chaining yang merupakan teknik pencarian dimulai dari fakta yang diketahui, kemudia mencocokkan fakta-fakta tersebut dengan bagian IF dari rule IF-THEN. Bila ada fakta yang cocok dengan bagian IF, maka rule tersebut dieksekusi sebagai penarik kesimpulan untuk mendiagnosa penyakit pada kambing.Aplikasi sistem pakar dibuat berbasis Android karena penggunanya yang banyak dan dapat mudah digunakan dimana saja dan kapan pun. Diharapkan aplikasi dapat memberikan solusi dan penanganan sementara pada ternak berupa panduan untuk mengantisipasi terjadinya kematian pada kambing sebelum ditanyakan langsung kepada seorang pakar untk penanganan lebih lanjut.Dengan adanya sistem pakar untuk diagnose penyakit pada kambing berbasis android ini maka memudahkan peternak dalam melakukan tindakan yang diperlukan secara tepat dalam menangani penyakit pada kambing.Kata kunci: Android, penyakit, sistem pakar, forward chaining, kambing, android, mobile ABSTRACTLow knowledge of goat disease in the community in an attempt to identify early disease affects decision-making independently. Dependence on the knowledge of an expert or veterinarian is very high, but its existence is not always present and very difficult to find, especially in rural areas. Coupled with cost issues and very inefficient in terms of time.Therefore in the study designed an expert system with forward chaining method which is a search technique starting from known facts, then match those facts with the IF part of the IF-THEN rule. If there are facts that match the IF section, then the rule is executed as a conclusion to diagnose the disease in goats.Expert system applications are made based on Android because of its many users and can be easy to use anywhere and anytime. It is expected that the application can provide solutions and temporary handling of livestock in the form of a guide to anticipate the occurrence of death in goats before being asked directly to an expert for further handling.With the expert system for diagnosis of disease in goats android-based this makes it easier for farmers in performing the necessary actions appropriately in dealing with disease in goats.Keywords : android, disease, expert system, forward chaining, goat, android, mobile.

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Sistem Pakar Diagnosa Penyakit Kulit Akibat Virus Menggunakan Teorema Bayes

Telematika ◽

10.31315/telematika.v15i2.3128 ◽

2018 ◽

Vol 15 (2) ◽

pp. 117

Author(s):

Putri Taqwa Prasetyaningrum ◽

Nuri Budi Hangesti

Keyword(s):

Expert System ◽

Skin Disease ◽

Skin Diseases ◽

Bayes Theorem ◽

Existing Problems

AbstractSkin is one of the most important organs in humans, because through the skin we can feel the feel and the surface of an object. If the skin is attacked, the disease may cause many consequences, such as from mild itching or to severe, the skin can not feel anything. Based on existing problems in the community created an application that can help people to recognize skin diseases suffered, so the level of awareness will keep the cleanliness higher, namely the application of expert system of viral skin disease using bayes theorem. In this research will be designed a system using method bayes theorem this expert system will be able to produce a diagnosis of skin diseases and treatment that needs to be done. With this application of course can help people to recognize the illnesses that have been allegedly allegedly to refer to injured. Based on 20 data that have been tested against experts and systems, for patients affected by viral skin diseases were 17 patients and those not infected were 3 patients. As for the suitability of testing between the validation results of experts (doctors) and the system, obtained percentage of 85%.Keywords: Skin diseases, Expert system, Teorema Bayes.AbstrakKulit adalah salah satu organ terpenting pada manusia, karena melalui kulit kita dapat merasakan rasa dan permukaan sebuah benda. Apabila kulit terserang penyakit maka akan banyak akibat yang akan ditimbulkannya, mulai dari yang ringan yaitu terasa gatal atau sampai yang berat yakni kulit tidak dapat merasakan apapun. Berdasarkan permasalahan yang ada di dalam lingkungan masyarakat diciptakan suatu aplikasi yang dapat membantu masyarakat untuk dapat mengenali penyakit kulit yang diderita, sehingga tingkat kesadaran akan menjaga kebersihan makin tinggi, yakni aplikasi sistem pakar penyakit kulit akibat virus. Pada penelitian ini akan dirancang sebuah sistem menggunakan metode Teorema Bayes. Sistem pakar ini nantinya dapat menghasilkan diagnosa penyakit kulit serta pengobatan yang perlu dilakukan. Dengan adanya aplikasi ini tentunya bisa membantu masyarakat mengenali penyakit yang dideritanya sehingga tersadar untuk merujuknya ke dokter ahli. Berdasarkan 20 data yang telah diujikan terhadap pakar dan sistem, untuk pasien yang terkena penyakit kulit akibat virus adalah 17 pasien dan yang tidak terkena infeksi adalah 3 pasien. Sedangkan untuk kesesuaian pengujian antara hasil validasi pakar (dokter) dan sistem, diperoleh tingkat persentase keberhasilan sebesar 85%.Kata Kunci : Penyakit kulit, Sistem Pakar, Teorema Bayes.

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Sistem Pakar Diagnosis Penyakit Jamur pada Manusia Menggunakan Input Suara Berbasis Android

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) ◽

10.29207/resti.v3i3.1187 ◽

2019 ◽

Vol 3 (3) ◽

pp. 435-442

Author(s):

Feriantano Sundang Pranata ◽

Jufriadif Na’am ◽

Sumijan

Keyword(s):

Expert System ◽

Early Detection ◽

Skin Disease ◽

Skin Diseases ◽

Initial Diagnosis ◽

Test Results ◽

Certainty Factor ◽

Early Diagnose ◽

The Tropics

Fungal skin disease is a type of disease that is often suffered people in the tropics. Phenomena in the community often assume that this disease will heal by itself. However, if left the effects of fungal skin disease can worsen the sufferer condition. The importance of early detection and treatment is very necessary, but this requires patients go to hospital or doctor so that patients spend a lot of time and money. For this reason, was build an android expert system with speech to early diagnose fungal skin diseases. From this initial diagnosis will save time and money and provide alternative prevention for sufferers. The method used in this study is the Certainty Factor of 20 patients. The accuracy of the test results to the system compared to the results of the doctor's diagnosis is 95%. So that, this expert system can be an early alternative in diagnose fungal skin diseases in humans.

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Automation Diagnosis of Skin Disease in Humans using Dempster-Shafer Method

E3S Web of Conferences ◽

10.1051/e3sconf/20183111006 ◽

2018 ◽

Vol 31 ◽

pp. 11006 ◽

Cited By ~ 1

Author(s):

Dyna Marisa Khairina ◽

Heliza Rahmania Hatta ◽

Rustam Rustam ◽

Septya Maharani

Keyword(s):

Infectious Disease ◽

Decision Tree ◽

Skin Disease ◽

Skin Diseases ◽

Automated System ◽

Forward Chaining

Skin disease is an infectious disease that is common in people of all ages. Disorders of the skin often occur because there are factors, among others, are climate, environment, shelter, unhealthy living habits, allergies and others. Skin diseases in Indonesia are mostly caused by bacterial, fungal, parasitic, and allergies. The objective of the research is to diagnose skin diseases in humans by using the method of making decision tree then performing the search by forward chaining and calculating the probability value of Dempster-Shafer method. The results of research in the form of an automated system that can resemble an expert in diagnosing skin disease accurately and can help in overcoming the problem of skin diseases.

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Application of Human Disease Diagnosis System Transmitted by Mosquito Vector Using Forward Chaining Method

JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) ◽

10.24843/jlk.2020.v08.i04.p08 ◽

2020 ◽

Vol 8 (4) ◽

pp. 421

Author(s):

Kevin Joel Purba ◽

I Made Widiartha

Keyword(s):

Skin Disease ◽

Human Disease ◽

Skin Diseases ◽

Disease Diagnosis ◽

Mosquito Vector ◽

Internal Organs ◽

Web Based ◽

Diagnosis System ◽

Forward Chaining ◽

Skin Symptoms

Disease is very easy to find in tropical countries including Indonesia. The skin itself is the most outermost organ that is easily attacked by the skin because the skin itself is an organ that is used to protect the internal organs. Many people do not consider how dangerous the skin disease is if it is not treated. Therefore, it is expected that with the advancement of technology, it can prevent the occurrence of skin diseases that can attack the community. In the research I did, I used the Forward Chaining Method. The system that I created is Web-based, where the system will issue a number of questions in the form of skin symptoms experienced by the user or patient and later when the patient has finished answering the question the system will process the patient's answer and finally the system will issue the answer being experienced by patients.

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Implementation of The Introduction of Skin Diseases Based on Augmented Reality

10.31219/osf.io/5yh4r ◽

2021 ◽

Author(s):

akuwan saleh

Keyword(s):

Augmented Reality ◽

Skin Disease ◽

Skin Diseases ◽

Negative Impact ◽

High Accuracy ◽

Health Conditions ◽

Test Results ◽

Tropical Country ◽

Java Programming ◽

Optimal Distance

Indonesia is a tropical country that has high rainfall. Environmental conditions greatly affect health conditions in humans such as skin health examples. Many people are still confused to identify the skin disease they are suffering from. This has a negative impact on people's lives. In this research, an application is made that is useful for introducing and informing various types of skin diseases with the Convolutional Neural Network (CNN) algorithm and implementation for information in introducing this skin disease using augmented reality (AR). This application is created using the Java programming language and is implemented on smartphones with the Android operating system. From the test results obtained, the classification results obtained when detecting skin diseases get conditions in accordance with or the same as the trained data. At a light intensity of 355 lux, the highest accuracy was obtained for measles skin disease. For the detection of skin diseases using different distances, the optimal distance to get a high accuracy value is the distance of 8 cm.

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