Kajian Model Hidden Markov Diskret dan Aplikasinya pada Harga Gabah Kering Panen
Ardana, N.K. Kutha
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A discrete hidden Markov model is a model which consists of the cause of event and observations process. This model assumes that the cause of event is Markov chain which is not observed directly. The observations process has discrete-range. Parameters of this model are transition probabilities and expectation of observations process. They are estimated by using the maximum likelihood method and expectation maximization algorithm. The estimation procedure involves change of measure. The estimation of parameters uses Mathematica 6.0, a functional programming based algebraic computer systems. The model is then applied to the price of harvest dry rice from January 2000 until March 2007. The estimated parameters are used to calculate expectation of harvest dry rice price. The result of this study shows that the discrete hidden Markov model can be applied to model the harvest dry rice price.