scholarly journals RANCANG BANGUN PROGRAM APLIKASI SISTEM PAKAR UNTUK DIAGNOSIS HAMA UTAMA KEDELAIUNTUK DIAGNOSIS HAMA UTAMA KEDELAI

2012 ◽  
Vol 21 (1) ◽  
pp. 11
Author(s):  
Atman Roja
Keyword(s):  
Expert System ◽  
Agricultural Technology ◽  
Soybean Plant ◽  
Yield Losses ◽  
Certainty Factor ◽  
Model Driven ◽  
Pest Infestation ◽  
Advanced User ◽  
User Friendly ◽  
Damage Symptoms

<div data-canvas-width="358.7930270399999">Pest infestation to soybean plant results in yield losses up to 80%. Therefore, it needs to be controlled properly. The main problem in controlling it is that far mers a nd ext ension workers a re difficult to promptly diagnose the types of main pest infecting the plant in the field. In consequence to the technology applied to control it is not appropriate. Whether it is mechanically, biologically, and chemically. To help them in making prompt decission, a user friendly tool need to be developed. One of the tools is an expert system. The development and implementation of the system were carried out at Indonesian Assessmetn Institute for Agricultural Technology (IAIAT) of West Sumatera Province and Universitas Putra Indonesia, Padang. The project was conducted from March to September 2009. The methodology applied in designing, developing, and implementing. The system was process-oriented methodology that is a model driven technique orienting to a process. The expert system generated uses based knowledge of 15 pests types attaching soybean plant, 7 sites of plant damage, 53 damage symptoms, and 166 nules. While the knowledge base is 15 technologies of main pest management having certainty factor/CF around 0.8 – 1.0. The system interface consists of two forms, that are one for advanced user and the another one for farmer or extension worker. The advanced one is able to improve the existing knowledge as well as the rules and the non advanced just consult to the system. The developed system need to be further developed to make it comprehensive. The system is also called “Sipakar Hatmalai”.</div>

scholarly journals An Application of Expert System to Identify Trees Utilizing Leaf Images

2007 ◽  
Vol 1 (2) ◽  
Author(s):  
Muhammad Lhsan Sarita ◽  
Sri Hartati
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
Data Base ◽  
Computer Programs ◽  
Forest Sector ◽  
Certainty Factor ◽  
Forward Chaining ◽  
Almost All ◽  
User Friendly ◽  
Leaf Image

AbstractTree identification is a very important to support almost all activities in the forest sector. Unfortunately, the inavailability of data and computer programs that is user friendly have caused ineficiency in tree identification. This research tries to make an expert system to identify trees by using the leaf images. To store the data in the knowledge base one must choose one of the some leaf images that are in the data base available in the program according the characteristic of the leaf. Each leaf image has a code and the accumulation of all codes build a tree code then this code is saved in the knowledge base. The tree code is used to identify a tree by making the comparison between input chosen by user and the tree code in the knowledge base using forward chaining. User who has information about a tree can add to the knowledge base but this information must be validated by an expert before it is used in the system. Another task of an expert is to give a CF (certainty factor) for each tree.The result of this research shows that no more errors are found due to input mistakes and the program is more user friendly. Another advantage is that the knowledge base is more flexible, dynamic and well organized Validation of knowledge base by experts can increase the quality and accuracy of using the knowledge base system.Keywords : expert system, leaf image, knowledge base, forward chaining, CF

Situsparu: Sistem Pakar Untuk Deteksi Penyakit Tuberkulosis Paru

2018 ◽  
Vol 10 (1) ◽  
pp. 41-47
Author(s):  
Ricky Surya ◽  
Dennis Gunawan
Keyword(s):  
Expert System ◽  
Tuberculosis Patient ◽  
The Body ◽  
Certainty Factor ◽  
Good Reliability ◽  
Delone And Mclean ◽  
The World ◽  
Index Terms ◽  
Manual Calculation ◽  
Tuberculosis Prevalence

Tuberculosis is an infectious disease caused by mycobacterium tuberculosis. It can affect some parts of the body: lungs, lymph nodes, intestines, kidneys, endometrium, bones, and brain. According to the survey of tuberculosis prevalence conducted by Republic of Indonesia Ministry of Health in 2013-2014, Indonesia was the second country in the world with the most case of tuberculosis. It makes Indonesia become a country with emergency in lungs tuberculosis. An expert system for lungs tuberculosis detection is built to help people detecting the possibility of suffering from lungs tuberculosis. Therefore, it is hoped that the lungs tuberculosis patient can have early treatment. Certainty factor is used to solve the uncertainty problem delivered by the doctor when examining the patient. Thus, certainty factor is an appropriate method to be used in the expert system for detecting certain disease. This method has been correctly implemented, proved by comparing system detection result to manual calculation result. The expert system has 81.25% accuracy, 83.49% success using DeLone and McLean model, and a cronbach alpha of 0.82 which indicates a good reliability based on the indicators used in the questionnaire. Index Terms— Certainty Factor, Disease Detection, Expert System, Pulmonary Tuberculosis, Situsparu

Sistem Diagnosa Hama Dan Penyakit Pada Tanaman Wortel Menggunakan Metode Certainty Factor

2018 ◽  
Vol 2 (2) ◽  
pp. 99-108
Author(s):  
Imelda Telaumbanua ◽  
Erwin Panggabean ◽  
Asaziduhu Gea
Keyword(s):  
Expert System ◽  
Pest Control ◽  
Plant Disease ◽  
Alternative Solution ◽  
Disease Symptom ◽  
Certainty Factor ◽  
Support Activity

Abstrak   Komputer saat ini merupakan perangkat yang sudah menjangkau hampir sebagian besar masyarakat. Kemajuan teknologi dalam bidang komputer telah menjadikan komputer sebagai alat bantu untuk memudahkan pekerjaan manusia dalam berbagai aspek. Salah satu contohnya menghasilkan suatu pendekatan utntuk dapat mengetahui jenis penyakit yang terserag pada tanaman dengan menggunakan metode Certainty Factor. Sistem ini, dapat membantu seseorang untuk mengetahui penyakit yang terserang berdasarkan gejala yang ada pada tanaman serta memberikan solusi untuk penaggulangan atau membasmi penyakit serta hama yang terdapat pada tanaman wortel dengan metode certainty Factor.Dalam  upaya pengendalian hama dan penyakit tanaman wortel secara strategis, seseorang pakar dibutuhkan  untuk bertindak sebagai media bantu, mengingat terbatasnya pengetahuan para praktisi petani wortel dalam mengetahui penyakit pada tanaman serta memberikan solusi kepada petani untuk membasmi penyakit yang terserang pada tanaman wortel.Sistem pakar tanaman memiliki tujuan mengetahui jenis hama dan penyakit, gejala, penyebab, pencegahan, dan menyediakan alternatif solusi penanggulangan hama dan penyakit pada setiap tanaman. Sistem pakar ini juga akan dapat membantu untuk mendukung aktivitas dalam pemecahan masalah.   Kata Kunci: Sistem Pakar, Wortel, Hama dan Penyakit, Certainty Factor, Web     Abstract   Computer current’s is device that has reach almost large part comumunity. Progress technology in subject computer has make computer as tool help for facilitate job human in various aspect. Either for example produce disease that stricken at plant with use method certinty factor. System’s, can help someone for know disease that stircken based on symptom that is at plant and give solution fo handling or eradicate disease and pest that there are at plant carrot with use method certainty factor. In effort pest control and plant disease carrot strategically, someone expert needed for act as media help, remember lomited knowedge some practitioner farmer carrot in know disease at plant and give solution to farmer to exterminate disease that stircken at plant carrot. Expert system plant have purpose know type pest and disease, symptom, cause, prevention and provide alternative solution handling pest and disease at every plant. Expert su=ystem this will can help for support activity in prevention problem.   Keywords: Expert System, Carrot, Pest and Disease, Certainty Factor, Web

Design Fuzzy Expert System And Certainty Factor In Early Detection Of Stroke Disease

2020 ◽  
Author(s):  
Laurentinus ◽  
Kiswanto ◽  
Rahmat Sulaiman ◽  
Fransiskus Panca Juniawan ◽  
Dwi Yuny Sylfania ◽  
...  
Keyword(s):  
Expert System ◽  
Early Detection ◽  
Fuzzy Expert System ◽  
Certainty Factor

scholarly journals Inheritance of Antibiosis Resistance to the Dectes Stem Borer, Dectes texanus, in Soybean PI165673

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 738
Author(s):  
Lina M. Aguirre-Rojas ◽  
Lawrent L. Buschman ◽  
Brian McCornack ◽  
William T. Schapaugh ◽  
Erin D. Scully ◽  
...  
Keyword(s):  
North America ◽  
Larval Stage ◽  
Stem Borer ◽  
Plant Introduction ◽  
Lower Number ◽  
Soybean Plant ◽  
Yield Losses ◽  
First Instar ◽  
Significant Yield ◽  
Antibiosis Resistance

Dectes texanus larvae girdles the stems of soybean and cultivated sunflowers causing significant yield losses in North America. The soybean Plant Introduction (PI) 165673 exhibits antibiosis resistance to the larval stage. The objectives of this study were: (1) to determine the inheritance of D. texanus resistance in PI165673; (2) evaluate PI165673 antibiosis resistance before 21 d post infestation; (3) evaluate girdling damage in PI16563 at the end of the season. K07-1544/PI165673 F2 and F2:3 populations were tested for resistance to D. texanus in 2011 and 2012, and PI165673 antibiosis resistance and girdling damage were evaluated in 2014. Segregation for resistance to D. texanus and heritability estimates in the F2 and F2:3 populations indicated that resistance was controlled by two genes with dominant and recessive epistasis. Antibiosis evaluations indicated: (1) PI165673 contained lower number of larvae and eggs relative to the number of oviposition punctures at 15 d post infestation; (2) the proportion of first-instar larvae was higher in PI165673 at 15 d post infestation; (3) larvae reach the sixth-instar stage in PI165673. None of the PI165673 plants were girdled at the end of the season. Identification of additional sources of D. texanus resistance is required to impair larval development in the stem.

scholarly journals Development of a Web Based Expert System for Rubber Crop Disease Diagnosis and Management

2018 ◽  
Vol 10 (3) ◽  
pp. 239-248
Author(s):  
S. Konyeha ◽  
F. A. Imouokhome
Keyword(s):  
Expert System ◽  
Disease Diagnosis ◽  
Field Extension ◽  
Rule Base ◽  
Destructive Effect ◽  
Web Based ◽  
Procedural Code ◽  
Base Engine ◽  
Crop Disease ◽  
User Friendly

An expert system imitates the decision–making adeptness of a human expert. They are intended to answer complicated questions characterized mainly as if–then rules instead of traditional procedural code. A major problem facing the cultivation of rubber (Hevea brasiliensis) in developing countries is the destructive effect of pathogens which result in about fifty percent (50%) loss in crop yield. This problem persists, due to a communication gap between agricultural researchers, such that field extension officers, and farmers are hampered by various operational and logistic challenges. This paper is an effort to bridge this gap, and hence features an expert system that can be accessed online by farmers.  The expert system allows farmers to select disease symptoms presented in categories from a JAVA based user friendly graphical interface. The output generated by the rule–base engine, diagnoses the diseases of the rubber crop, and suggests curative and preventive measures. The main source of information for developing the expert system’ knowledge–base was the Rubber Research Institute, Iyanomo, Edo State, Nigeria.

scholarly journals Sistem Pakar Diagnosa Penyakit Avian Influenza Pada Bebek Menggunakan Metode Certainty Factor

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Arief Gilang Ramadhan ◽  
Teguh Susyanto ◽  
Iwan Ady Prabowo
Keyword(s):  
Expert System ◽  
Avian Influenza ◽  
Prior Experience ◽  
Large Population ◽  
Animal Disease ◽  
Ordinary People ◽  
Certainty Factor ◽  
Bird Flu ◽  
Meat And Eggs

Ducks are widely farmed poultry animals, because of its large population, the disease is also caused a lot. In avian influenza disease is an infectious animal disease caused by a virus and can infect humans. Avian invluenza is also a cause of decreased quality of meat and eggs, can even cause death in ducks. Disease in ducks is difficult to know because people have no prior experience. Communities and breeders find it difficult to take appropriate action on ducks affected by avian influenza so that they can be fatal. During 2012 - 2017 there were 1856 cases of bird flu in Indonesia. In October 2017 there were 3 cases of avian invluenza. Where 900 ducks died. From the explanation above, an expert system is needed to diagnose avian influenza. This system can help ordinary people and farmers who do not have experience in dealing with avian influenza. Disease data and symptoms of avian influenza that will be entered into this expert system can be obtained from interviews with experts and see references of knowledge about duck symptoms. So that this expert system can help in dealing with AI disease. In testing the validity, the calculation of the system manually and from expert diagnosis are the same. So that this application is feasible to use for the community and breeders.

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