Judul: IPB (Bogor Agricultural University)
Abstrak: Penggunaan tepung daun katuk dalam ransum ayam petelur dapat menurunkan kandungan kolesterol telur dan meningkatkan intensitas warna kuning telur sedangkan pada ayam pedaging mampu meningkatkan kualitas karkas. Namun demikian, penelitian mengenai dinamika status kolesterol pada puyuh yang diberi daun katuk dalam ransum belum dilakukan.
Keyword: Performans kualitas telur, Dinamika status kolesterol, Tepung daun katuk

Judul: Kandungan Kolesterol, Lemak, Vitamin A dan E dalam Daging, Hati, dan Telur, serta Performa Puyuh dengan Pemberian Ekstrak dan Tepung Daun Katuk (Sauropus androgynus L. Merr) dalam Ransum
Abstrak: Daun katuk (Sauropus androgynus L. Merr) merupakan tanaman obat yang sudah banyak diteliti karena banyak manfaatnya. Beberapa manfaat daun katuk yaitu sebagai tanaman obat keluarga, bahan makanan yang bergizi tinggi, zat pewarna makanan, dan dapat memperlancar air susu ibu. Daun katuk memiliki kandungan serat kasar yang paling tinggi pada beberapa tanaman hijau bahan pakan (23,65%). Penggunaan daun katuk dalam pakan ternak dapat dibuat dengan beberapa metode yaitu dalam bentuk tepung dan ekstrak. Masing-masing metode memiliki keunggulan, bentuk tepung mudah dalam pembuatan tetapi serat kasar yang terkandung masih tinggi dan menjadi hambatan dalam pencernaan khususnya unggas. Bentuk ekstrak yang memiliki kemudahan dalam penyimpanan, dan dalam proses pembuatan ekstrak bertujuan untuk mengambil sebagian atau seluruh zat yang ada di dalam tanaman. Penelitian ini bertujuan untuk mengamati pengaruh perbedaan pemberian ekstrak tepung daun katuk (ETDK) yang dibandingkan dengan tepung daun katuk (TDK) melalui penilaian kandungan kolesterol, lemak, vitamin A dan E pada daging, hati dan telur, serta performa puyuh. Ransum perlakuan yang diberikan terdiri dari empat macam ransum, yaitu ransum basal (R0) sebagai ransum kontrol, R0 + 0,15% ETDK (R1), R0 + 0,30% ETDK (R2), R0 + 10% TDK (R3). Puyuh terbagi atas 4 perlakuan dan 4 ulangan dengan 13 ekor setiap ulangan. Data performa puyuh yang diperoleh dianalisis dengan Rancangan Acak Lengkap (RAL) dan diuji lanjut dengan uji jarak Duncan jika hasilnya berbeda nyata sedangkan data kandungan kolesterol, lemak, vitamin A dan E dianalisis secara deskriptif.
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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