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Abstract
ABSTRACT
Economic growth in the region is the regional economy conditions change continuously towards a better State for
a certain period. The slow economic growth became the latest leading indicator an area to develop. Indicators that
can be used for example, GDP and inflation. On the research of these indicators will be used to predict the growth
rate of the economy of Central Sulawesi province using the Backpropagation Neural Network Methods. Simulation
of the program in the form of input data is represented 𝑥1 and 𝑥2 and biased 𝑏1 dan 𝑏2 symbolized. With hidden
layers comprising 𝑧1, 𝑧2, 𝑧3, 𝑧4, … , 𝑧17 . and y as output. Based on the results and discussion has been done, can be
drawn the conclusion of process Neural Network prediction of Backpropagation with 1 hidden layer neurons and
the number 17 against 26 data represents data inflation and GDP of the year 2010 up to 2016 with sigmoid activation
function binner was able to predict the rate of economic growth with a prediction error of 16.66%.
Keywords : ANN, Backpropagation Method, Inflation, PDRB.
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