Judul: Kajian numerik model hidden markov satu waktu sebelumnya untuk nilai tukar Rupiah terhadap Dolar Amerika
Abstrak: Hidden Markov model is a model that consists of a pair stochastic processes, ie: the process of observation and the cause factors of the observation, where the cause factors of the observation are not observed directly and assumed to be a Markov chain. The previous time hidden Markov model is a hidden markov model that the observation process is influenced by current events and one previous time cause factors. The previous time hidden Markov model can be applied to the exchange rate of rupiah to US dollar, where the exchange rate of rupiah to US dollar is the observation and the contributing factor is a Markov chain. Parameters of the model are estimated using the maximum likelihood method and calculated using expectation maximization (EM) iterative algorithm. Using the initial value obtained by trial and error, Santoso (2008) was able to model the exchange rate of rupiah to US dollar with MAPE 14.58%. In this paper, the initial value is structuredly generated on a specific interval so that the accuracy of model increases. Retrieved MAPE is 4.13% with only one iteration.
Keyword: Bogor Agricultural University (IPB), the exchange rate of Rupiah, MAPE, hidden Markov model, EM algorithm

Judul: Pemodelan Nilai Tukar Rupiah terhadap Dollar Amerika Menggunakan Deret Waktu Hidden Markov Empat Waktu Sebelumnya
Abstrak: The exchange rate of Rupiah to US Dollar fluctuates according to time in a long period. An existing exchange rate might happen again in the future. Assume that the causes of the fluctuation are not observed directly and form a Markov chain, then the exchange rate of Rupiah to US Dollar can be modeled by the hidden Markov time series. In this research, the model used to describe the exchange rate of Rupiah to US Dollar is the four previous time in hidden Markov time series. This model assumes that the exchange rate of Rupiah to US Dollar depends on Markov chain explained by the cause of occurence and the four previous exchange rates of Rupiah to US Dollar. The model parameter is estimated by using the maximum likelihood method, while the estimation itself is calculated using the expectation maximization algorithm, which is implemented using Mathematica. After estimating the parameter, the exchange rate of Rupiah to US Dollar are calculated. The results are as follows. The symmetric mean absolute percentage error (SMAPE) is 2,1%, the maximum absolute error is 19,16%, the minimum absolute error is 0,0036%, and only 1,95% of the whole absolute percentage error that is bigger than 10%. These results show that the four previous time in hidden Markov time series can describe the exchange rate of Rupiah to US Dollar very well.
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Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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