scholarly journals Penerapan Metode Certainty Factor Dan Naïve Bayes Untuk Mendiagnosa Penyakit Akibat Gigitan Nyamuk

2020 ◽  
Vol 4 (2) ◽  
pp. 49-60
Author(s):  
Yudo Bismo ◽  
Giofani Harsanto
Keyword(s):  
Expert System ◽  
System Application ◽  
Naive Bayes ◽  
Human Life ◽  
Naïve Bayes ◽  
Application Software ◽  
Certainty Factor ◽  
Bayes Method ◽  
Initial Symptoms ◽  
Calculation Results

Health is the main point for the expensive human life. However, many stakeholders ignore their health, which in the end the disease they suffer is too late to be diagnosed, thus reaching a chronic stage that makes it difficult to treat. Same is the case with mosquito bites. The poor behavior of stakeholders toward healthy living habits, especially littering in gutters or in rivers, causes mosquitoes to form colonies by making their nests and environment dirty, dirty and unsightly. The initial symptoms that often arise from the bite of a dengue mosquito, malaria and chikungunya are generally the same and difficult to distinguish. To overcome the above problems, it is necessary to build a system where the system can help stakeholders to diagnose diseases caused by mosquito bites on android. The research method used in this research is the Research and Development method, because the final result of this research is to produce a product in the form of an expert system application software to diagnose diseases caused based mosquito bites by android. The results obtained in this study are by applying the certainty factor method in the application of this expert system is able to provide the percentage calculation results in detecting diseases caused by mosquito bites, while the naïve bayes method is able to detect the type of mosquito. The accuracy of the expert system application that has been made is 90% in diagnosing diseases caused by mosquito bites.

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 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 SISTEM PAKAR DIAGNOSA PENYAKIT DAN HAMA PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAIVE BAYES

2021 ◽  
Vol 2 (3) ◽  
pp. 390-398
Author(s):  
Bayu Bastiyan Suherman
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Preventive Measures ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Agricultural Commodities ◽  
Bayes Method ◽  
Mathematical Basis ◽  
Lack Of Information ◽  
Corn Plants

Corn is one of the leading agricultural commodities that can be used as a staple plant other than rice. Constraints faced by corn farmers include the lack of information about diseases that attack the corn plants, which causes less productivity. In this study a system was developed that can automatically detect disease that attacks corn plants so that preventive measures can be taken to prevent corn plants from dying. Expert systems are designed to solve certain problems by imitating the work of experts. In addition, this expert system also helps farmers who are experiencing problems regarding diseases and pests and their solutions without relying on an expert. The method used is the Naive Bayes method, Naive Bayes is a method used to predict probabilities and has several characteristics that are istitively in accordance with the way of thinking of an expert and accompanied by a strong mathematical basis. From the tests carried out with diagnoses obtained from the comparison between the results of expert diagnoses and the diagnosis of the system to diagnose diseases and pests in corn plants is 90%.

scholarly journals Application Of Naïve Bayes to Predict the Potential of Rain in Ternate City

2021 ◽  
Vol 328 ◽  
pp. 04011
Author(s):  
Alwin Ali ◽  
Amal Khairan ◽  
Firman Tempola ◽  
Achmad Fuad
Keyword(s):  
Test Data ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Training Data ◽  
Bayes Method ◽  
Calculation Results ◽  
Bayes Algorithm ◽  
Correct Data ◽  
Rain Data ◽  
Naive Bayes Method

The amount of rainfall that occurs cannot be determined with certainty, but it can be predicted or estimated. In predicting the potential for rain, data mining techniques can be used by classifying data using the naive Bayes method. Naïve Bayes algorithm is a classification method using probability and statistical methods. The purpose of this study is how to implement the naive Bayes method to predict the potential for rain in Ternate City, and be able to calculate the accuracy of the Naive Bayes method from system created. The highest calculation results with new data with a total of 400 training data and 30 test data, obtained 30 correct data with 100% precision, 100% recall and 100% accuracy and the lowest calculation results with new data with a total of 500 training data and 50 test data, obtained 38 correct data and 12 incorrect data with a percentage of precision 61.29%, recall 100% and accuracy 76%.

scholarly journals Development of Android-based Rabbit Disease Expert System

2018 ◽  
Vol 7 (4.44) ◽  
pp. 82
Author(s):  
Dyah Ayu Irawati ◽  
Yan Watequlis Syaifudin ◽  
Fabiola Ester Tomasila ◽  
Awan Setiawan ◽  
Erfan Rohadi
Keyword(s):  
Naive Bayes ◽  
Diagnostic System ◽  
Naïve Bayes ◽  
Certainty Factor ◽  
Bayes Method ◽  
Trust Value ◽  
User Input ◽  
Sample Data ◽  
Testing Data ◽  
Naive Bayes Method

Many rabbit keepers or breeders are panics when their rabbit has an illness. This paper proposed an expert diagnostic system application for Android-based rabbit disease using the Naïve Bayes method to determine the illness and Certainty Factor for the trust value of the condition by combining the rate of the trust of users and experts due to diagnose the diseases of the rabbit.The testing was using 65 data learning and 160 data learning to test the naïve Bayes method. Furthermore, the certainty factor is using CF user 1 and its variation.The results obtained for 65 data learning is 53%, while 160 data learning is 73%. With the naïve Bayes method, it can be concluded that the more data learning, the better and more accurate the system. The results of conformity with the testing data obtained from the variative CF user value, namely 53% accordingly, 13% inappropriate, 33% near. The effect of compliance with the sample data collected from the CF value of user 1 is 53% appropriate, 7% inappropriate, 40% is near. With the certainty factor method, it can be concluded that differences in user input values affect the overall CF value. 

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 Sistem Pakar Diagnosa Virus Corona Dengan Metode Naïve Bayes

2021 ◽  
Vol 9 (1) ◽  
pp. 81
Author(s):  
Fareza Aditiyanto Nugroho ◽  
Arif Fajar Solikin ◽  
Mutiara Dwi Anggraini ◽  
Kusrini Kusrini
Keyword(s):  
Expert System ◽  
Natural Disaster ◽  
Naive Bayes ◽  
Virus Disease ◽  
Diagnostic System ◽  
Naïve Bayes ◽  
The Body ◽  
Human Being ◽  
Bayes Method ◽  
The World

Humans being are faced with non-natural disasters which have bad effect for population on the world. This non-natural disaster is called Corona Virus Disease (COVID-19). This COVID-19 will become a pandemic in 2020. This types of COVID-19 is coming from the Orthocronavirinae. It belongs to the Coronaviridae and the Nidovirales. This type of that virus has caused some disease to birds, mammals and also human being. Therefore, the research was conducted. The result of this research will give the information about system which related the classification human being according to their transmission to the body. This research used naïve bayes method. The result of this research is diagnostic system with the level of accuracy 94%. Thus, COVID-19 diagnostic expert system used to know the level of COVID -19 infections to human being. It can help the user knowing the next treatment.Keywords : Expert System, Naïve Bayes, Coronavirus, Covid-19

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.

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