ANALISIS PEMBERIAN NUTRISI MENGGUNAKAN METODE FUZZY LOGIC STUDI KASUS TANAMAN CABAI

  • Devin Viondra Sihar Matondang Universitas Prima Indonesia
  • Delmanto Saogo Universitas Prima Indonesia
  • Rizki Samuel Putra F. Sianturi Universitas Prima Indonesia
  • Sopian Dapit Universitas Prima Indonesia
  • Ertina Sabarita Barus Universitas Prima Indonesia

Abstract

This research addresses the challenges faced by chili farmers in predicting harvest outcomes and providing nutrition according to plant needs. The Fuzzy Logic Mamdani method is proposed as a decision support system to determine the optimal nutrient application volume based on soil conditions, temperature, and acidity level (pH). By synthesizing fuzzy logic, this study aims to assist chili farmers in optimizing harvest results through appropriate nutrient application. The research methodology involves literature review, observation, and data collection to form a dataset with variables such as irrigation volume, soil moisture, temperature, and soil pH. The research results include the formation of fuzzy sets, application of implication functions, rule composition, defuzzification, and irrigation volume calculations. Simulations using the Fuzzy Logic Toolbox show that the Fuzzy Logic Mamdani method can provide predictions of nutrient application volumes that align with chili plant conditions. In testing, when the input variable of water content is 35.6 at a temperature of 30.8 with a soil pH of 3.7, the system recommends an irrigation volume of 204, categorized as high. The findings of this research can serve as a predictive tool to help chili farmers determine the optimal nutrient application volume based on environmental conditions.

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Published
2023-12-27
How to Cite
MATONDANG, Devin Viondra Sihar et al. ANALISIS PEMBERIAN NUTRISI MENGGUNAKAN METODE FUZZY LOGIC STUDI KASUS TANAMAN CABAI. Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 6, n. 2, p. 408-416, dec. 2023. ISSN 2621-3079. Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/929>. Date accessed: 05 mar. 2024. doi: https://doi.org/10.37600/tekinkom.v6i2.929.
Section
Articles