Mushliha

Evaluation of ARIMA, ARIMA-LSTM, LSTM, and CNN-LSTM Models for Daily Air Quality Index Forecasting in Jakarta

Findings indicate that deep learning approaches, particularly CNN-LSTM, are more effective in capturing the complex dynamics of urban air pollution data and have strong potential to support air quality forecasting and pollution control systems in Jakarta.