Expert System to Predict Acute Inflammation of Urinary Bladder and Nephritis Using Naïve Bayes Method

2021 ◽  
Author(s):  
Ria Arafiyah ◽  
Diyah Anggraeny ◽  
Rachel Haryawan ◽  
Zakiyah Hamidah
Keyword(s):  
Expert System ◽  
Urinary Bladder ◽  
Acute Inflammation ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Naive Bayes Method

scholarly journals Rancangan Aplikasi Sistem Pakar Diagnosa Penyakit Mononukleosis Dengan Metode Naive Bayes

2020 ◽  
Vol 7 (3) ◽  
pp. 403
Author(s):  
Rizky Hasanah Restari ◽  
Sinar Sinurat ◽  
Suginam Suginam
Keyword(s):  
Expert System ◽  
Health Center ◽  
Naive Bayes ◽  
Disease Diagnosis ◽  
Naïve Bayes ◽  
The Other ◽  
Daily Activities ◽  
Bayes Method ◽  
Other Hand ◽  
Naive Bayes Method

Health is one of the important factors for carrying out daily activities. However, some people do not care about the health of their bodies so that in the end many diseases that are diagnosed late cause the condition at a serious stage. One of the diseases in question is mononucleosis. In general, if the community is exposed to symptoms of mononucleosis, they will go to the nearest hospital or health center to do the examination. But on the other hand they have to sacrifice enough time for that. For this reason, it is necessary to make an application for a disease diagnosis expert system for the community as a means of overcoming these problems. With this design, an expert system of mononucleosis is produced, where this system uses the naive bayes method and the doctor's knowledge into the system. This expert system will produce output / output in the form of the diagnosis of mononucleosis

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 Perbandingan Naïve bayes dan Certainty factor pada Sistem Pakar Untuk Mendiagnosa Dini Penyakit Glaukoma

2020 ◽  
Vol 5 (3) ◽  
pp. 291
Author(s):  
Hanif Rahman Burhani ◽  
Iskandar Fitri ◽  
Andrianingsih Andrianingsih
Keyword(s):  
Expert System ◽  
Naive Bayes ◽  
Comparison Method ◽  
Naïve Bayes ◽  
Training Data ◽  
Certainty Factor ◽  
Bayes Method ◽  
Lack Of Information ◽  
Statistics And Probability ◽  
Naive Bayes Method

Glaucoma is an eye disease that causes the second largest blindness after cataracts, this disease can cause decreased vision and can even be fatal, namely permanent blindness if it is not realized and treated immediately. Lack of information and education to the public to always maintain eye health is the basis for the purpose of making this expert system which aims to provide early diagnosis to people who are indicated to have glaucoma based on the symptoms or characteristics previously felt. The Naïve bayes method is a method that uses statistics and probability in predicting a person's chance of suffering from glaucoma based on the symptoms previously felt. It is made based on a website with PHP as the programming language and uses MySQL for the database. As for the comparison method used is the Certainty factor, which is a method that functions to determine a certainty value based on the calculation of the predetermined CF value by applying manual calculations. In the Naïve bayes method, the application can group symptom data and types of disease and can diagnose based on previous training data, while for the Certainty factor method based on the calculation of the value of the expert and the CF value that has been inputted by the user, it can produce a percentage of the diagnosis of the disease glaucoma in 96%.Keywords:Certainty factor, Expert System, Glaucoma, MySQL, Naïve bayes, PHP.

scholarly journals The diagnose of oil palm disease using Naive Bayes Method based on Expert System Technology

2018 ◽  
Vol 1007 ◽  
pp. 012015 ◽  
Author(s):  
Marlince Nababan ◽  
Yonata Laia ◽  
Delima Sitanggang ◽  
Oloan Sihombing ◽  
Evta Indra ◽  
...  
Keyword(s):  
Expert System ◽  
Oil Palm ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
System Technology ◽  
Bayes Method ◽  
Naive Bayes Method

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 Sistem Pakar Untuk Mendeteksi Kerusakan Komputer Dengan Metode Naive Bayes

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Suleman - AMIK BSI Tegal ◽  
Saghifa Fitriana - STMIK Nusa Mandiri Jakarta ◽  
Tri Chanda Putra - AMIK BSI Purwokerto
Keyword(s):  
Expert System ◽  
Programming Language ◽  
System Application ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Initial Diagnosis ◽  
Correct Solution ◽  
Bayes Method ◽  
The Public ◽  
Naive Bayes Method

Abstract With the rapid technology of today, making computers very important in the daily. Using computers without proper maintenance often damages your computer. Of these problems, people are often confused. Therefore, this expert system application has been developed to help the public identify symptoms of computer damage as well as solutions to overcome the damage. In the development of this expert system with naive Bayes method, with the collection of data in use is interview and observation. This expert system application is based on Android using the basic programming language. In designing this expert system application, the user can choose the symptoms of damage to the computer in the natural, then the resulting output is a possibility of damage experienced by the hardware, after which the user can see an explanation of how the damage solution must be solved. The solution is that this expert system can naturally perform the initial diagnosis through the symptoms of the computer and then provide the correct solution step in overcoming the problem. Keywords: Expert System, The Computer Expert, Android, Naïve Bayes Abstrak Dengan pesatnya teknologi saatini, khususnya komputer sangat berpengaruh dalam kehidupan sehari-hari. Penggunaan komputer secara terus menerus tanpa adanya perawatan yang benar dapat membuat komputer mengalami kerusakan. Dari masalah tersebut sering membuat masyarakat merasa kebingungan. Oleh karena itu aplikasi sistem pakar ini di buat untuk membantu masyarakat dalam mendeteksi gajala-gejala kerusakan komputer yang dialami serta solusi untuk mengatasi kerusakan tersebut. Dalam pembangunan sistem pakar ini menggunakan metode naive bayes, Dengan pengumpulan data yang di gunakan yaitu wawancara dan observasi. Aplikasi sistem pakar ini di bangun berbasis android dengan bahasa pemrogram basic. Dalam perancangan aplikasi sistem pakar ini user dapat memilih gejala-gejala kerusakan pada komputer yang di alami, kemudian output yang dihasilkan adalah berupa kemungkinan kerusakan yang dialami oleh hardware, kemudian user dapat melihat penjelasan solusi cara mengatasi kerusakan tersebut. Adapun solusi yang diperoleh yaitu sistem pakar ini dapat melakukan diagnosis awal melalui gejala yang di alami komputer dan kemudian memberikan langkah solusi yang tepat dalam mengatasinya. Kata Kunci: Sistem Pakar, Pakar Komputer, Android, Naive Bayes

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 Expert System Using Naive Bayes Method in Identifying Caries Disease in Human Teeth

2021 ◽  
pp. 231-236
Author(s):  
Tio Ramadan Sapto Hari ◽  
S Sumijan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Tooth Decay ◽  
Test Results ◽  
Bayes Method ◽  
Human Teeth ◽  
The Public ◽  
Naive Bayes Method

Caries disease in human teeth is a disease that permanently destroys the inner walls of teeth and forms small holes in the teeth. The Indonesian people lack the knowledge to find information and identify tooth decay, which makes many people unaware of the consequences and dangers of this disease. Tooth decay disease is usually caused by three factors. The first factor is teeth and saliva, which are the hosts of microorganisms in the oral cavity. Bacteria and food are the second and third factors. The purpose of this research is to help the public find information about tooth decay, thus forming a branch of artificial intelligence, the expert system. Artificial intelligence is a science that allows you to build computer systems that display intelligence in different ways. An expert system is a computer program or information system that uses some knowledge of an expert. The methods used in this study are the Naive Bayes method and the model's view controller, which are implemented as a database in the PHP Codeigniter framework and MySQL. The data processed in this study is knowledge about the symptoms of dental caries obtained from experts. The test results of this method provide patients with the knowledge necessary to prevent tooth decay, with an accuracy rate of 83.61%. This expert system helps the public to recognize and obtain information about tooth decay. The Expert System can also be used to take the first step in preventing tooth decay.

scholarly journals PENGEMBANGAN SISTEM CERDAS UNTUK PREDIKSI DAFTAR KEMBALI MAHASISWA BARU DENGAN METODE NAIVE BAYES (STUDI KASUS: UNIVERSITAS PENDIDIKAN GANESHA)

2020 ◽  
Vol 3 (1) ◽  
pp. 22-34
Author(s):  
Komang Aditya Pratama ◽  
Gede Aditra Pradnyana ◽  
I Ketut Resika Arthana
Keyword(s):  
Naive Bayes ◽  
Intelligent System ◽  
Naïve Bayes ◽  
The State ◽  
State University ◽  
Bayes Method ◽  
New Students ◽  
Computer Based ◽  
Entrance Test ◽  
Naive Bayes Method

Ganesha University of Education or Undiksha is one of the state universities in Bali, precisely in the city of Singaraja. In the admission of new students, Undiksha applies 3 admissions paths, as follows the State University National Admission Selection (SNMPTN), State University Joint Entrance Test (SBMPTN), and Independent Entrance Test (SMBJM) consisting of 2 parts namely Computer Based Test (CBT) and Interests and Talents. Each year the committees are busy with the re-registration of prospective students. In determining the number of students quota for re-registration, they are still using the manual method in form of an excel file, so they want to use a system to do the process. These problems can be overcome by using “Intelligent System for Re-Registration of New Students Prediction using the Naive Bayes Method (Case Study: Ganesha University of Education)”. The Naive Bayes method is used to determine the re-register probability of the new students so that the number of students who re-register can be determining the new students quota. In developing the system, the researcher use the CRISP-DM methodology as a standard of data mining process as well as a research method. The results of this prediction system research show that the system can predict well with the average predictive system accuracy value of 75.56%.

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