Kombinasi Fuzzy Sugeno dan Profile Matching Dalam Pemilihan Pestisida Tanaman Padi Berbasis Android


Authors

  • Alpath Abimanyu Universitas Islam Negeri Sumatera Utara, Medan, Indonesia
  • Muhammad Fakhriza Universitas Islam Negeri Sumatera Utara, Medan, Indonesia
  • Muhammad Dedi Irawan Universitas Islam Negeri Sumatera Utara, Medan, Indonesia

DOI:

https://doi.org/10.30865/klik.v4i1.938

Keywords:

Sugeno; Profile Matching; Pesticides

Abstract

Rice is a plant that is very susceptible to attack by pests. There are various types of pests that can attack rice. Each attack has different symptoms and of course will require different pesticide handling, so a decision support system is needed in choosing the right pesticide. Pesticides are currently very important in their use in a plant, especially in rice plants. Farmers in Rumbia Village really need pesticides for their rice plants. So that the rice they plant is not attacked by pests which causes the rice to fail to harvest. The choice of pesticides greatly affects the yields of rice plants for farmers in Rumbia Village. However, farmers in Rumbia Village have not been optimal in determining the best pesticides for rice plants. The purpose of this study is to determine a decision support system in selecting the best pesticides for rice plants. By using the Fuzzy Sugeno algorithm and Profile Matching in determining the calculation of the best pesticide yields on rice plants. The system was built using the programming language Java, PHP and MySQL as the database. Meanwhile, in developing the system, the writer uses the Rapid Application Development and Unified Modeling Language (UML) methods as system design. The final results of this study are a decision support system for selecting the best pesticides for rice plants in Rumbia village based on android that can be used by the community, especially for them. Farmers in Rumbia Village in choosing pesticides for their rice plants.

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ARTICLE HISTORY


Published: 2023-08-20
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Issue

Vol. 4 No. 1 (2023): Agustus 2023

Section

Articles

Copyright (c) 2023 Alpath Abimanyu, Muhammad Fakhriza, Muhammad Dedi Irawan

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