CALENDAR VARIATION MODEL FOR FORECASTING TIME SERIES DATA WITH ISLAMIC CALENDAR EFFECT - Suhartono (LPPM Universitas Terbuka, 2006)
The aim of this paper is to develop a statistical model for explaining and forecasting the time series that contains Islamic Calendar effect. In time series literature, calendar variation is defined as a periodic and recurrent pattern with variation length period that usually caused by cultures and religions of people in a certain area. In Indonesia, the effect of the Eids holiday in many daily activities, such as transportation, inflation and consumption, is one example of calendar variations. This holiday happens on different month after three years or shift to previous month after at the same month on three years. This paper evaluates the disadvantage of seasonal classical time series model, such as Winter’s, Decomposition and ARIMA models, and develops a Calendar Variation model for forecasting time series that contain Islamic Calendar Effect. In this research, a real data about monthly sales of sardines are used as a case study. The results show that classical time series models, such as Winter’s, Decomposition and ARIMA models, cannot describe the calendar variation effect and yield invalid and unreliable forecast, particularly at the time (month) when the calendar variation happens. On the contrary, Calendar Variation model is a model that can explain precisely the impact of the calendar variation effect and gives valid and reliable forecasts.