scholarly journals Design of Expert System for Digestive Diseases Identification Using Naïve Bayes Methodology for iOS-Based Application

Jurnal INFORM ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 92-98
Author(s):  
Dewi Salma Salsabila ◽  
Rinabi Tanamal
Keyword(s):  
Expert System ◽  
System Application ◽  
Digestive Disease ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Disease Identification ◽  
Digestive Diseases ◽  
Accuracy Level ◽  
Before And After ◽  
Precise Prediction

Shown symptoms in digestive diseases might be similar, resulting in patient’s suspected diseases before and after diagnosis attempt might turn out to be different. This paper aims to build a design of an expert system for digestive disease identification using Naïve Bayes methodology for iOS-based applications. The result from this paper helps medical interns to increase the accuracy in predicting patient’s suspected digestive disease. A precise prediction in suspected disease identification can minimalize unnecessary diagnosis attempts, which saves time and reduces cost. Naïve Bayes is chosen because it has a higher accuracy level than other classification methods. This research includes collecting data through literature reviews on digestive diseases and their symptoms, processing the data to be turned into a knowledge base for the expert system, conducting data training using Naïve Bayes by the designed expert system application through this research. The result from the conducted data training using Naïve Bayes methodology shows that the expert system application has a higher accuracy level, which is 84%.

scholarly journals Design of Expert System for Digestive Diseases Identification Using Naïve Bayes Methodology for iOS-Based Application

Jurnal INFORM ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 92
Author(s):  
Dewi Salma Salsabila ◽  
Rinabi Tanamal
Keyword(s):  
Expert System ◽  
System Application ◽  
Digestive Disease ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Disease Identification ◽  
Digestive Diseases ◽  
Accuracy Level ◽  
Before And After ◽  
Precise Prediction

Shown symptoms in digestive diseases might be similar, resulting in patient’s suspected diseases before and after diagnosis attempt might turn out to be different. This paper aims to build a design of an expert system for digestive disease identification using Naïve Bayes methodology for iOS-based applications. The result from this paper helps medical interns to increase the accuracy in predicting patient’s suspected digestive disease. A precise prediction in suspected disease identification can minimalize unnecessary diagnosis attempts, which saves time and reduces cost. Naïve Bayes is chosen because it has a higher accuracy level than other classification methods. This research includes collecting data through literature reviews on digestive diseases and their symptoms, processing the data to be turned into a knowledge base for the expert system, conducting data training using Naïve Bayes by the designed expert system application through this research. The result from the conducted data training using Naïve Bayes methodology shows that the expert system application has a higher accuracy level, which is 84%.

scholarly journals Developing an Expert System Application to Detect Childs' Lung Disease

2020 ◽  
pp. 285-290
Author(s):  
Sulis Sandiwarno
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Support Vector Machine ◽  
Expert System ◽  
Expert Systems ◽  
Lung Disease ◽  
System Application ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Support Vector

The development of information technology has supported many activities, especially in terms of health. Artificial Intelligence (AI) is the application of information technology that is currently developing well. Several previous studies have evaluated models from expert systems to diagnose lung disease in children using Naïve Bayes (NB) and Support Vector Machine (SVM). However, in conducting these evaluations they do not try to make an integrated application to facilitate evaluation. In this study we propose to build a system that integrates NB and SVM classifiers. Furthermore, in this study we used a sample of data from a clinic in Indonesia. The results of this study, we conclude that the existence of this system will make it easier to evaluate the lung disease experienced by children.

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 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 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 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 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

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