ANALISIS INTERVENSI FUNGSI STEP (Studi Kasus Pada Jumlah Pengiriman Benda Pos Ke Semarang Pada Tahun 2006 – 2011)

Abstract

Data time series yang dipengaruhi oleh beberapa kejadian yang disebut intervensi akan mengakibatkan perubahan pola data pada satu waktu t. Analisis intervensi terdiri dari dua fungsi yaitu fungsi step dan fungsi pulse.

Time series data that are influenced by several events called the intervention will lead to changes in the pattern of data at a t time. Analysis of intervention consists of two functions, that is the step function and pulse function. Intervention of step function represents an intervention that have long-term effects, whereas pulse function represents an intervention that takes place at a particular time. Step function intervention model was created based on the delay time of the intervention (b), the length of the intervention effect (s), and the pattern of intervention effects that was occured after b + s period (r). Intervention modeling was done after ARIMA (Autoregressive Integrated Moving Average) model was acquired. ARIMA model was used to determine the b, s, and r order of intervention. In this study, the step function intervention analysis was used to assess the amount of postage on the period January 2006 to February 2011. Based on the analysis, the ARIMA model produced was ARIMA (0,1,1). Based on intervention response obtained residual value b = 4, s = 0, r = 2 is used to form a model of intervention using the least squares method.