Fletcher-reeves algorithm for predicting the quantity of production tomato plants in indonesia
DOI:
https://doi.org/10.35335/computational.v11i3.47Keywords:
Tomato Plant, Artificial Neural Network, Fletcher-Reeves, Prediction, ProductionAbstract
The growth of Indonesia's tomato plants continues to increase, and this increase needs to be balanced, according to data from 2015 to 2020. Tomatoes should be used all the time, even in Indonesia. Tomatoes are not only edible but also good for your health and appearance. For the government and various conferences to include this as a point of view in dealing with this problem, it is important to look at the amount of tomato production in Indonesia. Data from the Central Statistics Agency was used to obtain statistics on tomato plant cultivation in Indonesia from 2015 to 2020. This data is solved using the Fletcher-Reeves algorithm using architectural models 2-10-1, 2-20-1, 2-30-1, and 2-35-1. Model 2-10-1 is the best architectural model to predict the amount of tomato production compared to other models, according to the training and testing results of the four models. Model 2-10-1 is used to measure the accuracy of the Fletcher-Reeves method, with MSE Training set at 0.00008463 and MSE Testing at 0.0006094.
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