Analisis Prediksi Kasus DBD Berdasarkan Faktor Cuaca Dengan Multivariat ARIMA
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Abstract
Indonesia is facing a severe public health issue with dengue hemorrhagic fever (DHF). Anyone, including toddlers and adults, can be affected by DHF. Several weather factors, including humidity, air temperature, air pressure, and wind speed, contribute to frequent rainfall. ARIMA (Autoregressive Integrated Moving Average) is a time series method commonly used in research. To incorporate independent variables, multivariate ARIMA was employed. The analysis results revealed that weather factors, namely humidity, and Precipitation, have a linear relationship with DHF cases. The accuracy evaluation kof the applied model yielded an Mean Absolute Error (MAE) value of 18.12. The prediction estimates that the number of cases will peak in April 2023 and then decline to its lowest point in December 2023. For future development, it is necessary to enhance the quality of the data used to generate more significant results. Consequently, further evaluation is essential to achieve a smaller MAE value.
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