Sistem Pakar Mendiagnosis Hama Dan Penyakit Tanaman Terong Berbasis Web
Abstract
Abstract-- Eggplant is one type of fruit plants that can be processed into vegetables to be consumed as supporting energy in the human body, although this type of plant is not a basic necessity but always in demand by household consumers as a feeding menu enhancer. The eggplant does not necessarily grow and thrive. Based on observations in this season, many farmers suffer damage to the eggplant until the eggplant dies and cause crop failure. Facts show that eggplant plants have a wide range of distractions for survival and development. In recent seasons farmers have detected natural disruption of plants with the facts that occur in plants and also conduct preventive techniques naturally, because there is no system to be a consulting container for farmers who can help in detecting pests and diseases especially in eggplant plants. In this issue researchers do a study by designing a system based to diagnose the problem of crop disorders. The method used in this system is forward chaining method with best-first search technique. This web base system can be used to find solutions for farmers in controlling pest and disease problems. In the design of this system researchers use the programming language Unified Modeling Language (UML) such as Use Case Diagram, Activity Diagram, Sequence Diagram, Class Diagram in Model groove on the system. PHP programming language, MySql, PhpmyAdmin. This web-based system is presented to the farmer community in order to use the most reliable control in crop interference. Based on the results of a system test it can be proved that this web-based pest and disease system is running properly and deserves to be used. Keywords: Expert system, forward chaining, eggplant, diagnosis
Published
Jul 1, 2020
How to Cite
NDRURU, Ebitwan Famati Saro; YENNI, Yusli.
Sistem Pakar Mendiagnosis Hama Dan Penyakit Tanaman Terong Berbasis Web.
Journal Information System Development (ISD), [S.l.], v. 5, n. 2, july 2020.
ISSN 2528-5114.
Available at: <https://ejournal-medan.uph.edu/index.php/isd/article/view/391>. Date accessed: 29 mar. 2023.
Section
Artikel
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