Prediction Fuzzy Implementation in Monitoring System Based On Humidity, Soil Quality, And Environmental Conditions
DOI:
https://doi.org/10.62535/fffrrw78Keywords:
Environmental Conditions, Fuzzy Logic, Matlab, Soil FertilityAbstract
This research aims to evaluate the quality of soybean plant growth by considering three main factors: moisture content, light intensity, and soil pH. The Mamdani method is used as a system approach to optimize the processing of collected data for plant growth support. Measurements were taken using a sampling method to analyze the data comprehensively. In this experiment, moisture content, light intensity, and soil pH were measured to create optimal conditions for soybean plant growth. The implementation of the Mamdani method in this system is done by classifying inputs, such as data on water content, light intensity, and soil pH used during the planting period, then producing outputs based on experiments conducted according to predetermined criteria. Furthermore, comparisons are made to the samples to get the results of data analysis. This method can provide recommendations for optimizing environmental conditions for plants. By utilizing MATLAB application, accurate data analysis and visualization of results can be done efficiently. This research is expected to provide in-depth insight into the complex interactions between the three factors and their impact on soybean plant growth. This has significant implications for the development of sustainable agriculture and can provide valuable insights for farmers to improve soybean yields.
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