PERBANDINGAN METODE SARIMA DAN EXPONENTIAL SMOOTHING DALAM MEMPREDIKSI CURAH HUJAN DI KABUPATEN BANGKA TENGAH - Amanda, Madhania Fitri; Syafar, Muhammad; Wulandari, Jenny; Shavira, Novenda; Aulia, Hilda Marsyawa; Syahfitri, Delia; Dalimunthe, Dessy Yuliana (Fraction: Jurnal Teori dan Terapan Matematika, 2024)
Indonesia is a country that has a tropical climate because it is located on the equator. The tropical climate has two seasons, namely the dry season and the rainy season. Each region has a different climate intensity. Rainfall is one of the elements of weather and climate that has an influence on tropical areas such as Indonesia. To find out changes in rainfall patterns, predictions of the amount of rainfall are carried out using past data. In this research, rainfall prediction uses two methods, namely the Seasonal Auto Regressive Integrated Moving Average (SARIMA) method and exponential smoothing with rainfall data from 2018-2023. SARIMA is an ARIMA method that was developed to use data patterns that repeat seasonally. in a fixed time such as quarterly, semi-annually and annually. Exponential smoothing is a moving average forecasting technique that weighs past data exponentially so that the most recent data has a weight or greater in the moving average. Based on the results of the research, it was found that the best method between SARIMA and Exponential Smoothing Winters Additive was Exponential Smoothing Winters Additive with an RMSE value of 3.283.