Air Quality Forecasting in DKI Jakarta Using Artificial Neural Network

Abstract

The increase in the use of motorized vehicles increases air pollution conditions, especially in big cities such as the capital city of Indonesia, Jakarta. The pollution that pollutes this city contains various kinds of chemical particles that are harmful to living things when they enter the body. several efforts to reduce this pollution have been carried out, one of which is by identifying the pollutants contained in the air. This study uses data obtained from monitoring stations to predict the content of pollutants in the air at some time in the future. the method used is data mining forecasting with a neural network model. by using rapid miner obtained several graphic descriptions of pollutant conditions in Jakarta that go up and down. pollutant levels of SO₂, CO, PM10 and NO₂ all increased in the November-December period and at the same time period, ozone was at its lowest point. Results from Prediction air quality using Artificial Neural Network with 5 parameters, shown on this pollutant PM10 had an RMSE of 9,477; SO₂ had an RMSE 5,474; CO had an RMSE 8,392; O₃ had an RMSE 18,250; NO₂ had an RMSE 5,171. Can be concluded that the RMSE value of O₃ is higher than the others and the lowest value of NO₂.