ANALISIS NEURAL NETWORK STRUKTUR BACKPROPAGATION SEBAGAI METODE PERAMALAN PADA PERHITUNGAN TINGKAT KEMISKINAN DI INDONESIA
Abstract
Poverty is a condition in which people lack ability in traditionally devoted their primary. (Boa,2008) defines "Structural poverty is poverty, suspected uncaused structure from the condition of structures, or unfavorable life order". The expected amount of poverty can be reduced. In order to reduce the number of poverty to be known beforehand what factors are the cause of the poverty level is high or low. With the Backpropagation Neural Network structures for forecasting the calculation of the poverty level in Indonesia. Based on the analysis carried out apparently backpropagation neural network method yields more accurate in forecasting the calculation of the poverty level in Indonesia because these methods do training repeatedly to get the best models and can also be analyzed mathematically.
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