PENERAPAN BACKPROPAGATION DALAM MEMPREDIKSI PRODUKSI KELAPA SAWIT UNIT KEBUN MARJANDI
DOI:
https://doi.org/10.30865/komik.v3i1.1693Abstract
Oil palm plantations are one of the types of plantation crops that occupy an important position in the agricultural sector in general, and the plantation sector in particular ". This is because of the many plants that produce oil or fat. Production is obtained through a process that is quite long and full of risk. Here the author applies a Backpropagation method in which the method is part of supervised learning that is usually used for layers to determine the weights associated with neurons in the hidden layer. Which Backpropagation method will be virtualized into matlap program and will produce valid calculations. From the results of testing the Palm Oil Planting Year Production Report obtained in the 3-8-8-1 architecture which shows the target is reduced by the output jst that SSE 0.02976 which shows that there is an increase in the number of palm oil production as a target. From the data obtained, that the performance calculation of artificial neural networks with Backpropagation Algorithm is 67%.
Keywords: Backpropagation, Oil Palm Plantations, Palm Oil Production, The Marjandi Garden UnitReferences
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