Judul: Penyelesaian Model Tahap Terhingga dan Takhingga pada Proses Keputusan Markov dan Aplikasinya di Bidang Pertanian.
Abstrak: Markov decision process is a decision making process using Markov chain for stochastic models. The aim of this paper is to formulate a stochastic model involving states, actions and rewards. Further, the model is applied into agricultural sector, especially on determination of the optimal revenue based on actions specified. Also to determine an optimal policy that maximizes the reward. The methods used in this study are the complete enumeration, the policy iteration and the linear programming methods. Among the methods used, the most efficient method is the policy iteration. Based on the data used, determination of the policy using those three methods concluded that farmers would not use fertilizer when the soil fertility is good, and will use fertilizer when the soil fertility are moderate or low. Especially, for the case of the discount 0.7, the agricultural problem resulting the same policy with the case of no discount rate.
Keyword: policy iteration., Markov decision process, linear programming, enumeration

Judul: Kajian Model Hidden Markov Diskret dan Aplikasinya pada Harga Gabah Kering Panen
Abstrak: 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.
Keyword: Markov chain, Discrete hidden markov model, Expectation maximization algorithm

Judul: Karakteristik Anatomi Skelet Kepala Buaya senyulong (Tomistoma schlegelii).
Abstrak: Buaya sepit atau senyulong (Tomistoma schlegelii) merupakan jenis buaya asli Indonesia yang berhabitat di sungai-sungai Sumatera, Kalimantan, dan juga pedalaman Sulawesi. Salah satu ciri khas buaya senyulong adalah bentuk moncong yang runcing dan sempit, namun hingga saat ini informasi mengenai struktur skelet kepala buaya senyulong sangat terbatas. Penelitian ini bertujuan untuk mempelajari karakteristik anatomi skelet kepala buaya senyulong yang dikatikan dengan fungsi dan perilakunya. Penelitian dilakukan secara eksploratif dengan melakukan pengamatan, pencatatan, dan pengambilan gambar dari skelet kepala buaya senyulong. Skelet kepala berukuran panjang 70 cm, lebar 29 cm, dan tingggi 17 cm dengan permukaan kasar pada os nasale, os frontale, os maxilla, os mandibula, os lacrimale, os jugale. Jumlah gigi pada buaya ini sebanyak 78 buah, terdiri dari 4 buah gigi premaxila, 16 buah gigi maxila, dan 19 buah gigi mandibula. Pada regio orbitalis ditemukan dua pasang fenestrae temporales yang berkembang baik. Fenestra supratemporale merupakan lubang oval yang membentang di sepanjang os parietale. Fenestra infratemporale berbentuk segitiga dan dibatasi oleh os squamosum, os postorbitale, os jugulare, dan os quadratum. Os mandibula hewan ini mempunyai symphysis mandibularis yang panjang yaitu garis yang melintang di corpus mandibulae. Secara fungsional ukuran symphysis mandibularis berkaitan dengan adaptasi hewan terhadap diet makan.
Keyword: kepala, moncong, Tomistoma schlegelii