scholarly journals Diagnosa Penyakit Tanaman Cabai menggunakan Metode Forward Chaining dan Naïve Bayes

2021 ◽  
Vol 5 (2) ◽  
pp. 164
Author(s):  
Riyo Efendi ◽  
Fauziah Fauziah ◽  
Aris Gunaryati
Keyword(s):  
Expert System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Plant Diseases ◽  
Web Based ◽  
Bayes Methods ◽  
Forward Chaining ◽  
Speed Up ◽  
Handling Methods ◽  
The Web

The purpose of this research is to design a web-based expert system application to provide information about chili plant diseases and to diagnose the symptoms of diseases that attack chili plants and to provide solutions for appropriate handling methods, which can be accessed anywhere and utilized by the wider community and can speed up the time to deal with diseases that attack chili plants. This study uses the Forward Chaining and Naïve Bayes Methods in order to know the facts/signs of chili disease so that you can get the best quality chili. Based on the results of the discussion and calculation of the web-based expert system for diagnosing chili disease using the Forward Chaining and Naïve Bayes methods, it can be concluded that a simple application it can make it easier for users to diagnose chili disease and find out the causes and solutions. And can find out the total number of all comparisons of the 2 methods.Keywords:Chili disease, Expert System, Forward Chaining, Naïve Bayes.

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

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.

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.

scholarly journals Sistem Pakar Diagnosa Gangguan Hiperaktif Pada Anak Dengan Metode Naive Bayes Berbasis Web

2019 ◽  
Vol 3 (2) ◽  
pp. 90
Author(s):  
Yunia Ervinaeni ◽  
Aziz Setyawan Hidayat ◽  
Eri Riana
Keyword(s):  
Expert System ◽  
System Application ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Web Based ◽  
The Public ◽  
Hyperactivity Disorder ◽  
Psychiatric Problems ◽  
Naive Bayes Method

Disorder concentration attention or better known as ADHD (Attention Deficit Hyperactivity Disorder) is one of the main psychiatric problems that are often found in children. Hyperactive disorders are usually seen in children and as we get older the more difficult to deal with. There were 3 hyperactive disorders taken in this study namely hyperactivity, Impulsivity, Inattetion (Personality Problems). To help diagnose these hyperactive disorders, an expert system application is made to diagnose hyperactive disorders in children that can facilitate the public in diagnosing hyperactive disorders in children. Making this web-based expert system application uses the Naive Bayes method. The Naive Bayes method is a simple opportunity classification based on the application of the Bayes theorem with the assumption that between variables (independent) the presence or absence of a particular event from a group is not related to the presence or absence of other events. The final results are given in the form of a percentage of the diagnosis of hyperactivity in children.

scholarly journals Penerapan Metode Forward Chaining dan Naïve Bayes Untuk Mendiagnosa Penyakit Tanaman Kakao

2021 ◽  
Vol 5 (3) ◽  
pp. 979
Author(s):  
Hilman Hadi ◽  
Ucuk Darusalam ◽  
Andrianingsih Andrianingsih
Keyword(s):  
Information Dissemination ◽  
Naive Bayes ◽  
Economic Value ◽  
Agricultural Extension ◽  
Naïve Bayes ◽  
Plant Diseases ◽  
Bayes Method ◽  
Forward Chaining ◽  
The Many ◽  
Naive Bayes Method

Cocoa is one of the many plantation products in Indonesia which has considerable economic value, and has plantation land and its production each year has increased significantly. The lack of agricultural extension experts in providing direction, guidance, and information dissemination about the development of cocoa plant diseases faced by the cultivators of these plants can have an impact on the cultivators. The method used in this research is the forward chaining and naïve Bayes method. This system is expected to be useful for users in diagnosing cocoa diseases independently, of course easily and efficiently without having to require experts in their fields, with reference to the results and discussions carried out, the accuracy of this system has an accuracy value of about 95% in carrying out the diagnosis

scholarly journals Rancang Bangun Sistem Pakar untuk Penanganan Penyakit Pada Durian Berbasis Web

2021 ◽  
Vol 2 (1) ◽  
pp. 167-172
Author(s):  
Alfi Syahrinur Sitorus ◽  
Juna Eska ◽  
Sumantri Sumantri
Keyword(s):  
Expert System ◽  
Qualitative Approach ◽  
Plant Diseases ◽  
Certainty Factor ◽  
Web Based ◽  
Existing Problems ◽  
Factor Method ◽  
System Method ◽  
Manual Methods ◽  
The Web

Abstract :In cultivating durian farmers often suffer losses because durian plants are always attacked by pests and durian plant diseases because farmers still use manual methods to find out in dealing with durian plant diseases. From the existing problems, the purpose of this study is to design an expert system with Certainty factor method in handling web-based durian plant diseases that can be accessed by anyone. The benefits of this research provide convenience and help farmers to consult those who have activities worthy of a very experienced system such as experts. The expert system method used is using Certainty factor. The research methodology used by using a qualitative approach. The location of this research was conducted at the Asahan District Agriculture Service specifically in the field of plantations. The design model uses the Rad model, the programming language used by PHP and MySQL as its database. The results of this study are expected by the application of an expert system using the web-based Certainty factor method to diagnose diseases in durian plants and provide treatment solutions so that it can make it easier for farmers and communities to deal with diseases in the durian plants.                                       Keywords: Expert System; Durian; Certainty factor  Abstrak: Dalam membudidayakan durian petani selalu merasa rugi disebabkan tanaman durian selalu diserang para hama dan penyakit tanaman durian dikarenakan mereka tetap memakai cara yang kuno saat mendeteksi serta mengatasi penyakit tanaman durian. Dari permasalahan tersebut jadi tujuan penelitian ini agar merancang sistem pakar dengan metode Certainty factor pada penanganan penyakit tanaman durian berbasis web yang dapat diakses oleh siapa saja. Manfaat dari penelitian ini memberikan serta mempermudah juga menolong para petani ketika bertanya, juga mempunyai aktifitas seperti sistem yang handal bagaikan para ahli. Metode sistem pakar yang digunakan menggunkan Certainty factor. Metodeologi penelitian yang dipakai dengan mengguna-kan kualitatif. Tempat penelitian ini berada pada Dinas Pertanian kabupaten Asahan khusus nya dibidang perkebunan. Model perancangan menggunakan model Rad, bahasa pemograman yang dipakai php dan MySQL menjadi penyimpanan data nya. Hasil akhir dari penelitian ini diharapkan dengan adanya aplikasi sistem pakar memakai cara Certainty factor berjalan di web dapat mendiagnosa penyakit pada tanaman durian dan memberikan solusi penanganannya sehingga dapat lebih memudahkan petani dan masyarakat dalam menangani penyakit pada tanaman durian tersebut. Kata Kunci : Sistem Pakar; Durian; Certainty Factor

scholarly journals An Expert System for the Prognostication of the Brain and Nerve Diseases in Children with Convulsion Signs Based on Certainty Factors (Preprint)

2018 ◽  
Author(s):  
Narges Roozitalab ◽  
Hamid Nemati
Keyword(s):  
Expert System ◽  
Naive Bayes ◽  
Neurological Diseases ◽  
Naïve Bayes ◽  
Rule Based ◽  
Forward Chaining ◽  
Two Systems ◽  
The One ◽  
Time Required ◽  
Expert Physician

BACKGROUND Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. OBJECTIVE Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. METHODS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. RESULTS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors. CONCLUSIONS Nowadays, the importance of the treatment of neurological diseases in children is well known to everybody. Currently, there are only 60 neurological specialists in Iran. Due to the lack of necessary equipment, we need to send lab. Samples to the countries which have advanced laboratories for diagnosis. Therefore, a diagnostic expert system can significantly prevent deaths of children. In this paper, we design and implement a rule-based expert system in CLIPS language using certainty factors and forward chaining inference in order to help physicians. Naïve Bayes and Logistic algorithm and the experiences of the expert person have been considered to estimate the certainty factors. The accuracy of this system is 94% for detecting diseases. Performances of these two systems are compared and the results confirm that the certainty factors that are specified by the expert physician have 6.2 percent prediction improvement over the one with Naïve Bayes. It is worth noting that an automatic rule generating program has been developed to reduce the time required to produce rules manually and minimize errors.

Implementasi Metode Forward chaining dan Certainty factor dalam Mendiagnosa Autisme Anak Berbasis Web

2021 ◽  
Vol 5 (4) ◽  
pp. 362
Author(s):  
Tasha Fitria Kusumanagara ◽  
Fauziah Fauziah ◽  
Deny Hidayatullah
Keyword(s):  
Expert System ◽  
Autism Diagnosis ◽  
Certainty Factor ◽  
Literature Study ◽  
Web Based ◽  
Forward Chaining ◽  
Factor Method ◽  
Interview Methods ◽  
Collection Methods ◽  
The Web

Lack of parental or community knowledge of the symptoms of autism in their children results in neglected early detection. This of course can be too late in the treatment of autism in the future. Therefore, this study aims to design a web-based expert system for diagnosing children's autism. The development model used to design an autism expert system in children is a waterfall and implements the forward chaining method and the certainty factor method. While the data collection methods consisted of interview methods and literature study methods. From the results of the calculation test, it is concluded that the results of manual calculations and the web-based application of an expert system for autism diagnosis in children are the same as the results of the 98% confidence level. With this web-based autism expert system in children, it is hoped that it can help parents or the community to detect autism in their children early on.Keywords:Autism, Expert System, Web Based, Forward chaining Method, Certainty factor Method.

scholarly journals Design of Expert System for Diagnosis of Gonorrhea Disease by using Web-Based Naïve Bayes Method

2021 ◽  
Vol 3 (2) ◽  
pp. 223-233
Author(s):  
Teri Ade Putra ◽  
Raja Ayu Mahessya ◽  
Pradani Ayu Widya Purnama ◽  
Reza Suriadinata
Keyword(s):  
Expert System ◽  
System Application ◽  
Naive Bayes ◽  
Transmitted Disease ◽  
Naïve Bayes ◽  
The Body ◽  
Bayes Method ◽  
Web Based ◽  
The Public ◽  
Naive Bayes Method

Gonorrhea is a sexually transmitted disease caused by the bacterium Neisseria gonorrhea that infects the lining of the bladder, cervix, rectum, throat, and the whites of the eyes. This disease is spread through the bloodstream to other parts of the body, especially the skin and joints and is generally transmitted through sexual contact. Gonorrhea not only affects adult men and women, but babies and even newborns can get gonorrhea from their mothers. An expert system is a system that seeks to adopt human knowledge into computers, so that computers can solve problems like an expert. With this expert system, the public can obtain information or can solve the problems they face which can only be obtained with the help of experts in their fields. This study explains how the expert system diagnoses Gonorrhea using the Naïve Bayes method. By using the Naïve Bayes method, it can predict future probability values based on previous experiences experienced by people with gonorrhea, Document classification can be personalized, tailored to the needs of each person. By using this expert system application, it can provide information and make it easier for the public to be more familiar with Gonorrhea and can handle problems based on the expertise of doctors who are experts in their fields. This expert system can provide solutions and prevention of gonorrhea disease with the diagnosis process carried out efficiently and save time in helping the community in the prevention that occurs. This web-based expert system application is built with the PHP programming language and MySQL data storage.

scholarly journals SISTEM PAKAR MENDIAGNOSA PENYAKIT CAMPAK DAN RUBELLA DENGAN METODE FORWARD CHAINING BERBASIS WEB

2020 ◽  
Vol 3 (1) ◽  
pp. 51
Author(s):  
Asep Herman ◽  
Fungki Darmawan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Research Methods ◽  
Human Activities ◽  
Research Method ◽  
System Analysis ◽  
Web Based ◽  
Know How ◽  
Forward Chaining ◽  
The Web

Abstract:The development of technology is growing rapidly, one of which is to facilitate human activities by continuing to create new things such as Artificial Intelligence (AI) Systems that can help solve problems easily from the help of computers. The problem that will be discussed in this study is "The expert system for diagnosing measles and rubella using the web-based forward chaining method" is one part of AI, namely Expert System with the intend that users can know how much percentage of the disease they feel it.The research method used in this case refers to the journal "Pemanfaatan Sistem Inferensi Fuzzy pada Aplikasi Pendiagnosis Penyakit Kulit pada Anak" which is only to determine the value weight of symptoms of Measles and German Measles (Rubella) and for prevention or solutions that have been used briefly which comes from the source of articles on measles and rubella from alodokter.com and has been reviewed by Dr. Marianti. For research methods of system analysis using forward chaining method is useful for the running of symptom selection along with the weight of the values that have been determinedAt this conclusion the case discussed is useful for users who feel symptoms of Measles and Rubella and how to prevent it by using a website-based application. It should be noted that the discussion in this case is not to be the main reference in diagnosing measles and rubella and is not recommended to users who have measles and rubella with conditions that must be handled in an emergency.           Keywords : Expert system, Measles and German Measles (Rubella), forward chainingAbstrak: Perkembangan teknologi bertumbuh dengan cepat salah satu nya untuk mempermudah kegiatan manusia dengan terus menciptakan hal yang baru seperti Artificial Intelligence (AI) Sistem yang dapat membantu dalam menyelesaikan masalah dengan mudah dari bantuan komputer. Pada masalah yang akan di bahas pada penelitian kali ini adalah “Sistem pakar mendiagnosa penyakit campak dan rubella dengan metode forward chaining berbasis web” salah satu bagian dari AI yaitu Sistem Pakar dengan tujuan supaya pengguna dapat mengetahui seberapa peresentase penyakit yang dialami pengguna.Metode penelitian yang di gunakan pada kasus ini mengacu pada jurnal “Pemanfaatan Sistem Inferensi Fuzzy pada Aplikasi Pendiagnosis Penyakit Kulit pada Anak” yang hanya untuk mengetahui bobot nilai dari gejala Campak dan Campak jerman (Rubella) dan untuk pencegahan atau solusi yang di gunakan sudah di ringkas yang berasal dari sumber artikel campak dan rubella dari alodokter.com dan sudah ditinjau oleh dr. Marianti. Untuk metode penelitian pada analisis sistem menggunakan metode Forward Chaining berguna untuk berjalannya pemilihan gejala beserta bobot nilai yang sudah di tentukanPada kesimpulan kali ini kasus yang di bahas berguna bagi pengguna yang mengalami gejala pada penyakit Campak dan Rubella dan cara pencegahan nya dengan menggunakan aplikasi berbasiskan website. Perlu di ketahui pembahasan pada kasus ini tidak untuk menjadi acuan utama dalam mendiagnosa penyakit campak dan rubella dan tidak di anjurkan kepada pengguna yang mempunyai penyakit Campak dan Rubella dengan kondisi-kondisi yang harus di tangani secara darurat.Katakunci : Sistem Pakar, Campak dan Rubella, forward chaining

Sistem Pakar Mendeteksi Penyakit Tanaman Kelapa Sawit Menggunakan Metode Forward Chaining

2019 ◽  
Vol 1 ◽  
pp. 444
Author(s):  
Dimas Satria ◽  
Poningsih Poningsih ◽  
Widodo Saputra
Keyword(s):  
Expert System ◽  
Programming Languages ◽  
Palm Oil ◽  
Oil Palm ◽  
Oil Production ◽  
Plant Diseases ◽  
Accurate Information ◽  
Forward Chaining ◽  
Web Programming ◽  
Level Of Confidence

The purpose of this paper is to create an expert system to detect oil palm plant diseases in order to help farmers / companies in providing accurate information about the diseases of oil palm plants and how to overcome them and to help reduce the risk of decreasing palm oil production. This system is designed to mimic the expertise of an expert who is able to detect diseases that attack oil palm plants. The method used is forward chaining that is starting from a set of data and proving a fact by describing the level of confidence and uncertainty found in a hypothesis. The results of this study are to diagnose diseases of oil palm plants and their computerization using web programming languages.

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