DEPTH-FIRST SEARCH (DFS) METHOD FOR WEB-BASED DIAGNOSTIC DAMAGE TO RICE RICE PLANT

Khairani Putri Mirda; Arridha Zikra  Syah; Sahren

doi:10.20884/1.jutif.2022.3.1.154

Khairani Putri Mirda Sistem Informasi, Sekolah Tinggi Manajemen Informatika Dan Komputer Royal Kisaran, Indonesia
Arridha Zikra Syah Sistem Informasi, Sekolah Tinggi Manajemen Informatika Dan Komputer Royal Kisaran, Indonesia
Sahren Sistem Komputer, Sekolah Tinggi Manajemen Informatika Dan Komputer Royal Kisaran, Indonesia

DOI: https://doi.org/10.20884/1.jutif.2022.3.1.154

Keywords: Depth First Search, Expert System, Rice Pests

Abstract

Plants affected by pests will be more damaged if not treated early. Therefore, the farmer's diagnostic ability is needed for treatment as early as possible. For the needs of serious cases, the ability of experts is still expected. However, experts from the local Agriculture Service are not always available to assist in the diagnosis. So that the diagnosis can not be done as early as possible. One solution is to design an expert system for the early diagnosis of damage to lowland rice plants. The method used to solve is Depth First Search (DFS). The diagnosis process is done by answering questions about symptoms. Every question given by the system is the result of in-depth inference using the Depth First Search (DFS) method. The system can provide preventive or handling actions according to the results of the discovery of disturbing pests by the system. This expert system can diagnose symptoms of damage quickly, update knowledge according to the needs of experts.

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