Decision Support System for Determining the Best Pesticide for Rice Plants Using the Moora Method

Authors

  • Resvi Ansiska Universitas Putra Indonesia YPTK Padang
  • Eva Rianti Universitas Putra Indonesia YPTK Padang
  • Wifra Safitri Universitas Putra Indonesia YPTK Padang

DOI:

https://doi.org/10.35134/jcsitech.v9i4.89

Keywords:

Decision Support System, MOORA, Pesticides, Structured, Rice Plants

Abstract

completed quickly and performed effectively and efficiently, especially in the agricultural sector. Pesticides are chemical or organic substances that farmers use to protect rice plants from pests , so farmers often have difficulty choosing pesticides that will be used to prevent rice pests. In fact, the large number of pesticide products on the market and their very different advantages make farmers confused in determining pesticide choices. The Harapan Jaya farmer group always provides counseling and training regarding the management of agricultural products, therefore the farmer group continues to maintain rice production to avoid pests and there is no shortage of rice plants at this time by using pesticide products on the market. Decision Support Systems (DSS) are systems that are able to provide problem solving abilities and communication abilities for problems with structured and unstructured conditions. The method in the decision support system is Multi Objective Optimization on the basis of Ratio Analysis (MOORA). The results obtained from this calculation method are Rodenticide with a value of 0.288 which is ranked first and the fifth rank is Insecticide with a value of 0.047. By implementing a decision support system using the MOORA method, it is hoped that it will help select interconnected outputs, because the decision results are based on criteria data in determining the best pesticide for rice plants

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Published

2023-10-31

How to Cite

Ansiska, R., Rianti, E., & Safitri, W. . (2023). Decision Support System for Determining the Best Pesticide for Rice Plants Using the Moora Method. Journal of Computer Scine and Information Technology, 9(4), 204–209. https://doi.org/10.35134/jcsitech.v9i4.89

Issue

Volume 9 Issue 4 (2023): JCSITech

Section

Articles

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