Prediction of Gross Domestic Product (GDP) in Indonesia Using Deep Learning Algorithm

Abstract

Growth Domestic Product (GDP) is the important factor to know the stability of financial condition in a country. Regarding into GDP value could be known the economic condition per capita. Especially, during this pandemic situation, GDP need study further about its sudden fluctuation. The solution can be covered using the prediction approach. Deep learning as new method from machine learning schema had been observed in this research to cope the prediction of GDP problem. Two methods of deep learning techniques that were used, LSTM and RNN, shown that the prediction could fit the data actual very well. The accuracy at around 80% until 90% emerge from LSTM architecture 2 and RNN architecture 2. Based on this result, it could bring new perspective to use this model to know the GDP fluctuation in a country even in catastrophe of Covid-19.