Judul: Blood Metabolites Profile of Composite Sumatera Ewes Fed Flushing Ration
Abstrak: Penelitian ini bertujuan mengevaluasi pengaruh ransum flushing terhadap konsumsi nutrien dan metabolit darah induk domba komposit Sumatera pada fase pra-kawin dan pasca-kawin. Penelitian ini menggunakan 10 ekor domba komposit Sumatera yang telah beranak satu kali (rataan bobot badan 43,41, This research aims to evaluate the effect of flushing ration on nutrient intake and blood metabolites of composite Sumatera ewes at pre-mating and post-mating. This research used 10 composite Sumatera ewes that had given birth once (average body weight 43.41
Keyword: flushing, konsumsi nutrien, pasca-kawin, pra-kawin, reproduksi

Judul: Physiological Response and Estrus Characteristics of Sumatran Composite Sheep that Given Flushing Ration at the Sumatera Martabe Farm
Abstrak: Penelitian ini bertujuan mempelajari pengaruh ransum flushing terhadap respon fisiologis dan karakteristik estrus induk Domba Komposit Sumatera di Sumatera Martabe Farm. Jumlah domba yang digunakan sebanyak 10 ekor induk domba Komposit Sumatera yang memiliki rata-rata bobot badan 43,41 kg/ekor, ditempatkan pada kandang individu. Perlakuan yang diberikan meliputi 2 ransum, yaitu ransum kontrol (SMF) dan ransum flushing (Flushing). Peubah yang diamati adalah respon fisiologis, konsumsi nutrien berdasarkan bobot badan metabolis, dan karakteristik estrus (onset estrus, durasi estrus, dan respon estrus). Data yang diperoleh dianalisis dengan t-test independent sample menggunakan program IBM SPSS Statistic 25. Hasil penelitian menunjukkan ransum flushing yang digunakan berpengaruh nyata (P<0,05) meningkatkan konsumsi nutrien, dan mempercepat onset estrus dan durasi estrus dibandingkan dengan ransum SMF, namun tidak berpengaruh nyata terhadap respon fisiologis pada Domba Komposit Sumatera. Ransum flushing dapat meningkatkan konsumsi nutrien, mempercepat onset estrus dan durasi estrus , namun tidak mengganggu status fisiologis dari induk Domba Komposit Sumatera, This research aimed to study the effect of flushing rations on the physiological response and estrus characteristics of Sumatran Composite Sheep at the Sumatera Martabe Farm. A total of 10 Sumatran Composite Sheep with an average body weight of 43,41 kg/ekor, were used and placed in individual pens. The treatments consisted of 2 groups: a control ration (SMF) and a flushing (Flushing). The variables observes were physiological response, nutrient consumption based on metabolic body weight, and estrus characteristic (onset of estrus, duration of estrus, and estrus response). The data obtained were analyzed by independent sample t-test using the IBM SPSS Statistic 25 Program. The results show that flushing diet significantly (P<0,05) increased nutrient consumption and accelerated onset and duration of estrus compared to the SMF diet. However it, did not significantly affect the physiological response of Sumatra Composite Sheep. The flushing diet can enchance nutrient consumption, accelerate onset and duration of estrus, without disrupting the physiological status of Sumatra Composite Sheep.
Keyword: estrus, flushing, physiological response, sheep

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