Development of expert system for skin disease identification

Chili is an important commodity in Indoneisa’s economy. The fluctuating price causes chili to contribute to inflation for national economy. Chili’s price could increase because of demand in high level and production of chili in low level. The emergence of disease causes production of chili decreas. To solve the problem in chili disease, the disease needs to be diagnose as soon as possible. To diagnose the disease as soon as possible there is a need of chili expert system using android. Chili’s disease will be indentificated by inputting the symptoms which are shown by the plan. Expert system of chili plant disease identification design is based Android. Android Mobile is used as a device to insert the symptoms which are shown by the plant. The system will manage the symptoms that have been selected and show the diagnoses of the disease and how to control the disease. This system was designed using the Simple Additive Weighting (SAW) method and tested using Blackbox method. Testing using Blackbox method to show the system is able to identify the diseases of chili plant

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A Simplified Approach for Melanoma Skin Disease Identification

10.1109/icscan53069.2021.9526511 ◽

2021 ◽

Author(s):

G. Glorindal ◽

S. Arun Mozhiselvi ◽

T. Ananth Kumar ◽

K. Kumaran ◽

Phillip Chisomo Katema ◽

...

Keyword(s):

Skin Disease ◽

Simplified Approach ◽

Disease Identification ◽

Melanoma Skin

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A founder deletion of corneodesmosin gene is prevalent in Japanese patients with peeling skin disease: Identification of 2 new cases

Journal of Dermatological Science ◽

10.1016/j.jdermsci.2016.01.012 ◽

2016 ◽

Vol 82 (2) ◽

pp. 134-137 ◽

Cited By ~ 3

Author(s):

Kwesi Teye ◽

Yasushi Suga ◽

Sanae Numata ◽

Mikiko Soejima ◽

Norito Ishii ◽

...

Keyword(s):

Skin Disease ◽

Japanese Patients ◽

Disease Identification

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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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Comparative Study of Decision Tree, K-Nearest Neighbor, and Modified K-Nearest Neighbor on Jatropha Curcas Plant Disease Identification

Kinetik Game Technology Information System Computer Network Computing Electronics and Control ◽

10.22219/kinetik.v5i1.1012 ◽

2020 ◽

pp. 55-60

Author(s):

Triando Hamonangan Saragih ◽

Diny Melsye Nurul Fajri ◽

Alfita Rakhmandasari

Keyword(s):

Expert System ◽

Decision Tree ◽

Comparative Study ◽

Jatropha Curcas ◽

Plant Disease ◽

Nearest Neighbor ◽

Classification Methods ◽

K Nearest Neighbor ◽

Disease Identification ◽

Accuracy Result

Jatropha Curcas is a very useful plant that can be used as a bio fuel for diesel engines replacing the coal. In Indonesia, there are few plantation that plant Jatropha Curcas. But there is so limited farmers that understand in detail about the disease of Jatropha Curcas and it may cause a big loss during harvesting when the disease occured with no further action. An expert system can help the farmers to identify the lant diseases of Jatropha Curcas. The objective of this research is to compare several identification and classification methods, such as Decision Tree, K-Nearest Neighbor and its modification. The comparison is based on the accuracy. Modified K-Nearest Neighbor method given the best accuracy result that is 67.74%.

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Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Identifikasi Penyakit pada Paru

Jurnal Sistim Informasi dan Teknologi ◽

10.37034/jsisfotek.v3i2.111 ◽

2020 ◽

Author(s):

Ayu Prima Siska ◽

Yuhandri Yunus ◽

S Sumijan

Keyword(s):

Expert System ◽

Problem Solving ◽

Lung Disease ◽

Pulmonary Disease ◽

Human Knowledge ◽

Certainty Factor ◽

Human Organ ◽

Factor Method ◽

Disease Identification ◽

Certainty Level

Lungs are a very importand part of the human organ, which functions as a place for oxygen exchange. This organ that is located under the ribs has a very heavy task, as well as the pollution of the air we breathe everyday which will cause various diseases in the lungs. Lung disease is a disease that is common to everyone, and there are still many who are less concemed with lung healty, so that is causes many indications of lung diseas. Expert system is a system that uses human knowledge recorded in a computer to solve a problem. The purpose og this study was to datermine the accuracy of disease identification in the lungs using the Certainty Factor method. The date obtained is datae about the symptoms that prove wherher a person has lung disease or not and conduct an analysis of the date, so that later conclusions can be abtained from the facts found using an expert system of the Certianty Factor method. The date obtained is date about the sympyoms thet prove whethera person has lung as a problem solving metric which is a parameter value to show the amount of trust. The result of the research from an expert system on pulmonary disease with pulmonary tuberkolosis (TBC) with a certainty level og 68%. Expert system on lung disease using the Certainty Factor method can make it easien for sufferes to know and handle prevention and handling.

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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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FPGA based skin disease identification system using sift algorithm and K-NN

Twelfth International Conference on Digital Image Processing (ICDIP 2020) ◽

10.1117/12.2572951 ◽

2020 ◽

Author(s):

Joshua D. Mendoza ◽

Noel B. Linsangan ◽

Jumelyn L. Torres ◽

Emmanuel Luis Villanueva

Keyword(s):

Skin Disease ◽

Identification System ◽

Sift Algorithm ◽

Disease Identification

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