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

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%.

2020 ◽  
Vol 5 (3) ◽  
pp. 291
Author(s):  
Hanif Rahman Burhani ◽  
Iskandar Fitri ◽  
Andrianingsih Andrianingsih

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.


2020 ◽  
Vol 7 (3) ◽  
pp. 403
Author(s):  
Rizky Hasanah Restari ◽  
Sinar Sinurat ◽  
Suginam Suginam

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


2021 ◽  
Vol 9 (1) ◽  
pp. 81
Author(s):  
Fareza Aditiyanto Nugroho ◽  
Arif Fajar Solikin ◽  
Mutiara Dwi Anggraini ◽  
Kusrini Kusrini

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


2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Khoirunnisa devita Sari ◽  
Ade Eviyanti

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.


Author(s):  
Sulis Sandiwarno

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.


2018 ◽  
Vol 1007 ◽  
pp. 012015 ◽  
Author(s):  
Marlince Nababan ◽  
Yonata Laia ◽  
Delima Sitanggang ◽  
Oloan Sihombing ◽  
Evta Indra ◽  
...  

2019 ◽  
Vol 3 (2) ◽  
pp. 90
Author(s):  
Yunia Ervinaeni ◽  
Aziz Setyawan Hidayat ◽  
Eri Riana

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.


2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Suleman - AMIK BSI Tegal ◽  
Saghifa Fitriana - STMIK Nusa Mandiri Jakarta ◽  
Tri Chanda Putra - AMIK BSI Purwokerto

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


2020 ◽  
Vol 4 (2) ◽  
pp. 49-60
Author(s):  
Yudo Bismo ◽  
Giofani Harsanto

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.


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