Menentukan Parameter pada Model Arima (1,1,0) Box-Jenkins Menggunakan Estimasi Maksimum Likelihood

Abstract

Time series is assemble observation regularly in time. Time series is different becomes 2 that is time series stationary and time series non stationary. Time series non stationary that has stationaried by difference method known as ARIMA process. One of a model ARIMA called the ARIMA (1,1,0). The next step after we can determined the model that is estimation the parameters. General shape of likelihood function from ARIMA (1,1,0) Box Jenkins model can be done asumtion normally and independent in a t , so if the observation data has known then use the likelihood function for the parameter is: L(φ σ 2 , a │W)