PENENTUAN KOMODITI HORTIKULTURA BERDASARKAN KESESUAIAN LAHAN MENGGUNAKAN NEURO FUZZY SYSTEM

Publication Type:

Journal Article

Source:

Jurnal Teknologi, Volume 5, Number 1 (2012)

Keywords:

Hortikultura, Multilayer Perceptron, Neuro Fuzzy

Abstract:

Indonesia is rich a country in natural resources. Horticulture in particular, on, vegetables, fruit, chocolate, coffee, etc.. Is an export commodity that can improve the foreign exchange in the field of agriculture. In this research, modeling technology made in the field of intelligent systems is Neuro Fuzzy System for Horticulture and Plantation crops. The selected method using Multi Layer Perceptron (MLP) with Sigmoid activation function. Parameters of temperature, humidity, rainfall and altitude above the sea surface (DPL).
The output of the system of weights that will be tested by testing applications that require parameters that customize the fit menghasillkan commodity. Commodities are tested on the weighting at the end of training, namely bananas, oranges, mangosteen, mango, clove, coconut, coffee and chocolate. Hasill testing on 100 iterations to show the validity of 0.43 on a 0.9 threshold. Compliance with the output shown in the graph.

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