Dataset for Prediction of Acute Respiratory Infection (ARI) Cases in DKI Jakarta Using LSTM Based on Air Quality and Weather Conditions

This dataset contains daily time-series data regarding the number of Acute Respiratory Infection (ARI) cases, air quality indicators, and meteorological conditions in DKI Jakarta Province for the 2024–2025 period. This data repository was compiled to support the research titled "Prediction of the Number of Acute Respiratory Infection (ARI) Cases in DKI Jakarta Province Using Long Short-Term Memory (LSTM) Based on Air Quality Data and Weather Conditions." The repository consists of three data files representing each stage of pre-processing. The first file, `dataset_gabungan.xlsx`, contains raw data resulting from the merging of daily ARI case records, air quality parameters (such as PM2.5 and PM1), and weather conditions, organized by date. The second file, `dataset_ISPA_imputasi (5).xlsx`, is a dataset in which missing values for air quality and weather variables have been addressed using the Multivariate Imputation by Chained Equations (MICE) method. The third file, `dataset normalized.xlsx`, contains the final dataset transformed using the Min-Max Normalization method, making it ready for training models such as LSTM, XGBoost, and DLNM.