{"title":"用贝叶斯方法诊断木薯植物病害类型","authors":"Agung Purnomo Sidik","doi":"10.15575/JOIN.V4I2.379","DOIUrl":null,"url":null,"abstract":"This research was conducted to implement the Bayes algorithm in an expert system to diagnose types of diseases in cassava plants. The research data was taken from the Binjai City Agriculture and Fisheries Office in 2018. The expert system was built based on the web, where the application was built using the PHP programming language and MySQL DBMS. The results showed that the Bayes algorithm can be used in expert system applications to diagnose types of cassava plant diseases. In the Bayes algorithm, the knowledge base is taken from the data of the amount of data from cassava plants that suffer from disease, so the results of diagnosing cassava plants are based on existing data. Therefore, the more patient data that is used as a knowledge base, the better the diagnosis results are given.","PeriodicalId":53990,"journal":{"name":"JOURNAL OF INTERCONNECTION NETWORKS","volume":"5 1","pages":"69-74"},"PeriodicalIF":0.5000,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Diagnosis of Types of Diseases in Cassava Plant by Bayes Method\",\"authors\":\"Agung Purnomo Sidik\",\"doi\":\"10.15575/JOIN.V4I2.379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research was conducted to implement the Bayes algorithm in an expert system to diagnose types of diseases in cassava plants. The research data was taken from the Binjai City Agriculture and Fisheries Office in 2018. The expert system was built based on the web, where the application was built using the PHP programming language and MySQL DBMS. The results showed that the Bayes algorithm can be used in expert system applications to diagnose types of cassava plant diseases. In the Bayes algorithm, the knowledge base is taken from the data of the amount of data from cassava plants that suffer from disease, so the results of diagnosing cassava plants are based on existing data. Therefore, the more patient data that is used as a knowledge base, the better the diagnosis results are given.\",\"PeriodicalId\":53990,\"journal\":{\"name\":\"JOURNAL OF INTERCONNECTION NETWORKS\",\"volume\":\"5 1\",\"pages\":\"69-74\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2020-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JOURNAL OF INTERCONNECTION NETWORKS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15575/JOIN.V4I2.379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF INTERCONNECTION NETWORKS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15575/JOIN.V4I2.379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Diagnosis of Types of Diseases in Cassava Plant by Bayes Method
This research was conducted to implement the Bayes algorithm in an expert system to diagnose types of diseases in cassava plants. The research data was taken from the Binjai City Agriculture and Fisheries Office in 2018. The expert system was built based on the web, where the application was built using the PHP programming language and MySQL DBMS. The results showed that the Bayes algorithm can be used in expert system applications to diagnose types of cassava plant diseases. In the Bayes algorithm, the knowledge base is taken from the data of the amount of data from cassava plants that suffer from disease, so the results of diagnosing cassava plants are based on existing data. Therefore, the more patient data that is used as a knowledge base, the better the diagnosis results are given.
期刊介绍：
The Journal of Interconnection Networks (JOIN) is an international scientific journal dedicated to advancing the state-of-the-art of interconnection networks. The journal addresses all aspects of interconnection networks including their theory, analysis, design, implementation and application, and corresponding issues of communication, computing and function arising from (or applied to) a variety of multifaceted networks. Interconnection problems occur at different levels in the hardware and software design of communicating entities in integrated circuits, multiprocessors, multicomputers, and communication networks as diverse as telephone systems, cable network systems, computer networks, mobile communication networks, satellite network systems, the Internet and biological systems.
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