Judul: Konsumsi dan Kecernaan Nutrien dan Populasi Mikroba Feses Binturong (Arctictis binturong) di Taman Margasatwa Ragunan Jakarta
Abstrak: Tujuan penelitian ini adalah mempelajari konsumsi dan kecernaan nutrien dan populasi mikroba feses binturong di Taman Margasatwa Ragunan, Jakarta. Hewan yang digunakan adalah tiga ekor binturong, terdiri dari satu ekor betina dan dua ekor jantan. Analisis data yang digunakan dalam penelitian ini menggunakan metode statistika deskritif. Binturong mengkonsumsi 373,7±53 g.ekor-1.hari-1 pakan kering yang terdiri dari pisang siam sebagai sumber energi, telur ayam rebus dan karkas ayam sebagai sumber protein. Binturong mengkonsumsi 6.54±0.37 g.ekor-1.hari-1 PK, 1.39±0.22 g.ekor-1.hari-1 SK dan 13945.01±1782.68 kal EB. Nutrien yang dibutuhkan binturong adalah sebesar 1.77% PK, 0.37% SK, 4.97% NDF, 4.65% ADF dan 2.55% lignin+silika. Koefisien cerna (KC) pakan cukup tinggi, KC BK, BO, PK, SK, NDF, ADF dan lignin+silika, masing-masing sebesar 85.75%, 86.01%, 83.27%, 73.18%, 62.54%, 74.46% dan 78.43% dengan 11.71 Kkal.g.ekor-1.hari-1 DE dan 85.54% TDN. Populasi bakteri dan protozoa feses tidak dipengaruhi kondisi aerob dan anaerob ataupun perbedaan jenis kelamin.
Keyword: arctictis binturong, kecernaan, konsumsi, populasi mikroba

Judul: Konsumsi dan Kecernaan Nutrien dan Populasi Mikroba Feses Lutung Budeng (Trachypithecus auratus) di Pusat Primata Schmutzer, Ragunan, Jakarta.
Abstrak: Tujuan penelitian ini adalah mempelajari konsumsi dan kecernaan nutrien dan populasi mikroba feses lutung budeng di Pusat Primata Schmutzer, Taman Margasatwa Ragunan, Jakarta. Hewan yang digunakan adalah empat ekor lutung budeng, terdiri dari tiga ekor betina dan satu ekor jantan. Pakan yang diberikan memiliki kadar BK rendah, kecuali pisang kepok mentah dan ubi merah. Pakan mengandung 4.07%-36.81% PK, 11.43% SK, 18.25%-67.47% NDF, 2.40%- 29.3% ADF dan 2.7%-24% lignin+silika. Pakan yang digemari : pisang kepok mentah, ubi merah dan daun kumek, pakan yang kurang disukai : paprika. Nutrient yang dibutuhkan 16.25% PK, 13.67% SK, 17.1% NDF, 6.3% ADF dan 2.2% lignin+silica. Koefisien cerna (KC) pakan cukup tinggi, KC BK, BO, PK, SK, NDF, ADF dan lignin+silika, masing-masing sebesar 84.5%, 86.8%, 73.26%, 86.01%, 83.81%, 73.5% dan 35.5% dengan 2.78 Kkal.g.ekor-1.hari-1 DE dan 75.61% TDN. Kondisi anaerob dan aerob tidak mempengaruhi populasi bakteri; jenis kelamin tidak membedakan populasi bakteri dan protozoa feses.
Keyword: lutung budeng, konsumsi, kecernaan, populasi mikroba

Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm