Open AccessPrediksi Tingkat Pertumbuhan Ekonomi Provinsi Sulawesi Tengah Menggunakan Metode Backpropagation
Author(s) -
I M Jafaar,
Ali Sahari,
D Lusiyanti
Publication year - 2020
Publication title -
jurnal ilmiah matematika dan terapan/jurnal ilmiah matematika dan terapan
Language(s) - English
Resource type - Journals
eISSN - 2540-766X
pISSN - 1829-8133
DOI - 10.22487/2540766x.2019.v16.i2.14986
Subject(s) - backpropagation , inflation (cosmology) , artificial neural network , econometrics , inflation rate , statistics , computer science , economics , economy , mathematics , artificial intelligence , interest rate , macroeconomics , physics , theoretical physics
Economic growth in the region is the regional economy conditions change continuously towards a better State fora certain period. The slow economic growth became the latest leading indicator an area to develop. Indicators thatcan be used for example, GDP and inflation. On the research of these indicators will be used to predict the growthrate of the economy of Central Sulawesi province using the Backpropagation Neural Network Methods. Simulationof the program in the form of input data is represented 1 and 2 and biased 1 dan 2 symbolized. With hiddenlayers comprising 1, 2, 3, 4, … , 17 . and y as output. Based on the results and discussion has been done, can bedrawn the conclusion of process Neural Network prediction of Backpropagation with 1 hidden layer neurons andthe number 17 against 26 data represents data inflation and GDP of the year 2010 up to 2016 with sigmoid activationfunction binner was able to predict the rate of economic growth with a prediction error of 16.66%.Keywords : ANN, Backpropagation Method, Inflation, PDRB.