Machine learning of forecasting long-term economic crisis in Indonesia

Oil (energy) is huge influence of economic Indonesia. Since many sectors from Industries until individual need it. In fact, Indonesia is a country with high density population. Because of that, the necessity of oil must be meet amount of inhabitant in Indonesia. If government failed to answer the demand of oil, then Indonesia will be face economic crisis for long-term. So that, the forecast of it still need to be concerned. Furthermore, data about population and oil import were used to forecast economic condition. Shape of it had been done by machine learning. The result shows that the growth of population has influence of oil needed. Because when the population increases exponentially then the necessity of energy (oil) consumption followed. It roots of economic crisis in long-term. It can be proved from the accuracy result in training around 98%, while 90% in testing. By mean of that, Indonesia should concern more about population aging on economic growth refer to availability of oil. In other perspective, machine either show that the model forecast still find error. Error was caused by the use of few data; beside the aspect of economic is complex and chaos area.