ESTIMASI MAKSIMUM LIKELIHOOD PADA MODEL ANALISIS INTERVENSI MULTI INPUT FUNGSI STEP; (MAXIMUM LIKELIHOOD ESTIMATION IN STEP FUNCTION MULTI INPUT INTERVENTION ANALYSIS MODEL)

Hariadi, Wigid, Abdurakhman

2016 | Disertasi | FMIPA

ARIMA model is a popular model and is often used in time series analysis. This model is able to represent well on data that has a trend, a trend either up or down trend. However, the ARIMA model is no longer suitable for time series data if there is a change in the data that extreme (shock data), so that resulted in a change in the pattern of mean out of the ordinary. This data shock often occurs because of the intervention (the influence of external factors). Intervention analysis was used to evaluate the effects of external events on a time series data. In this paper, the authors wanted to model the impact of sea highway policies on stock price movements company in the field of shipping, in this paper were sampled stock of TMAS.JK. After analyzing the data, it is evident that the case of intervention on daily stock price TMAS.JK. Where intervention namely: interventions I, on August 11, 2014, allegedly as a result of the election of Jokowi-JK pair as President and vice President of Republic Indonesia on July 22, 2014. Interventions II, Jokowi speech at the APEC forum on marine highway program, and offers investment in the construction of ports to foreign nations on November 10, 2014. In this analysis, the authors use the method of maximum likelihood estimation ,where the models obtained is a ARIMA (2,1,0), first step function intervention (b=0, s=2, r=1), second step function (b=3, s=0, r=1).

Kata Kunci : intervention analysis; multi input; step function; maximum likelihood estimation.