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: Pemodelan nilai tukar Rupiah terhadap Dolar Amerika menggunakan Hidden Markov satu waktu sebelumnya
Abstrak: An exchange rate of Rupiah to American Dollar has become one of important reference for Indonesian economic movement. The movement of the exchange rate of Rupiah is an event that can occur anytime in a long period and possible to reoccur in the future. If the cause of event is not observed directly and forms a Markov chain, so the pair of the cause and an exchange rate of Rupiah can be modeled by hidden Markov. In this thesis the previous time hidden Markov model is used. This model assumes that the present exchange rate of Rupiah depends on the previous exchange rate of Rupiah and the present and previous cause. Model parameter is estimated by using maximum likelihood method and the calculation uses iterative algorithm expectation maximization (EM). Numerical computation is done by using Mathematica 10. After the parameter model is obtained, then the exchange rate of Rupiah to American Dollar can be estimated. Model accuracy is measured by using mean absolute percentage error (MAPE). Resulted MAPE is 4.48% with one iteration.
Keyword: Bogor Agricultural University, the exchange rate of Rupiah, hidden Markov model, MAPE, EM algorithm

Judul: Pengaruh Penambahan Azospirillum sp dan Mikroorganisme Selulolitik untuk Peningkatan Kadar Klorofil pada Bibit Kelapa Sawit.
Abstrak: Cocopeat merupakan material yang dapat digunakan sebagai media tanam dan tersedia dalam jumlah yang cukup banyak. Namun penggunaannya masih memerlukan penambahan pupuk. Hal tersebut dapat diatasi dengan menambahkan mikroorganisme ke dalam media tanam. Penelitian ini bertujuan melihat respon pertumbuhan tanaman dan kadar klorofil yang terbentuk pada bibit kelapa sawit melalui penambahan Azospirillum sp dan mikroorganisme selulolitik. Penelitian yang dilakukan meliputi seleksi isolat selulolitik, uji kompatibilitas antar isolat, pengamatan parameter pertumbuhan meliputi bobot kering, tinggi tanaman, panjang akar, jumlah daun, jumlah akar dan uji kadar klorofil daun. Hasil penelitian menunjukan bahwa formulasi isolat selulolitik yang dapat digunakan adalah isolat F77, F72, B33, dan B37. Parameter bobot kering memberikan hasil yang berbeda nyata pada perlakuan NFCL (mikroorganisme penambat nitrogen dan selulolitik (1:1) ) dibandingkan perlakuan lain dengan nilai 1.62 gram. Kadar klorofil total tertinggi didapatkan melalui perlakuan 2NFCL (mikroorganisme penambat nitrogen dan selulolitik (2:1) ) dengan nilai 0.28 mg/gram.
Keyword: bibit kelapa sawit, penambat nitrogen, selulolitik, cocopeat, klorofil