ANALISIS PERAMALAN CUACA KOTA SURABAYA MENGGAnalisis Peramalan Cuaca Kota Surabaya Menggunakan Pendekatan Autoregressive Integrated Moving Average (ARIMA) UNAKAN PENDEKATAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) - Latisa Alifa Maura; Nikmah Handayani; Devina Nadifa Nur Aulia; M. Al Haris (RAGAM: Journal of Statistics & Its Application, 2024)
Erratic weather is a crucial issue that can disrupt activities in all aspects. Weather monitoring needs to be done to avoid adverse consequences. ARIMA is one of the methods that can be used in weather forecasting because it is produce high accuracy, especially on short-term data. This research aims to get the best ARIMA model that produces accurate forecasting with the smallest error. Based on the research results, the best models obtained for temperature and humidity variables are (0,0,2) and (1,01) with MAPE values of 2.57% and 6.5%. Thus, the ARIMA model has very accurate forecasting performance.