Gross Domestic Product (GDP) is a benchmark for economic production conditions of a country. Estimates
of economic growth in the coming year in a country has important roles, among others as a benchmark in
determining business plans for business entities, and the basis for devising government fiscal policy.
Artificial Neural Network (ANN) has been increasingly recognized as a good forecasting tool in various
fields. Its nature that can mimic the workings of the human brain makes it flexible for non-linear and nonparametric data. GDP growth forecasting techniques using ANN has been widely used in various countries,
such as the United States, Canada, Germany, Austria, Iran, China, Japan and others. In Indonesia,
forecasting of GDP is only done by government institutions, namely National Planning Board, using
macroeconomic model. In this study, ANN is used as a tool for forecasting GDP growth in Indonesia, using
some variables, such as GDP growth in the two previous periods, population growth rate, inflation,
exchange rate and political stability and security conditions in Indonesia. Results from this study indicate
that ANN forecasts GDP relatively better than the one issued by the government. Further study would be to
use ANN to predict other economic indicators.
Keywords: GDP growth, ANN, Forecastin
