Judul: Patogenitas dan Imunogenitas Inokulasi Ookista Eimeria mivati Pada Ayam Pedaging
Abstrak: Penelitian ini bertujuan untuk rnelihat patogenitas dan imunogenitas akibat inokulasi Eimeria mivati isolat Bogor yang diinfeksi per oral pada dua kelompok umur ayam dengan berbagai dosis. Patogenitas tampak setelah infeksi pertama dengan menentukan penurunan bobot badan, persentase mortalitas, produksi ookista, histopatologi usus halus (jumlah parasit di usus, persentase kerusakan villi dan jumlah sel limfosit intraepitel), jumlah eritrosit dan leukosit ayam. lmunogenitas ditentukan setelah infeksi kedua dengan pengamatan yang serupa pada pengarnatan setelah infeksi pertama.
Keyword: 

Judul: Pengaruh inokulasi ookista Eimeria tenella (Railliet dan Lucet, 1891) pada gambaran darah ayam petelur jantan
Abstrak: Tujuan penelitian ini adalah mempelajari pengaruh inokulasi ookista Eimeria tenella pada gambaran darah ayam yang dilakukan secara artifisial. Pemeriksaan darah meliputi jumlah eritrosit, nilai hematokrit, kadar hemoglobin, jumlah lekosit serta diferensiasi lekosit. Sebanyak 200 ekor ayam petelur Hy-line jantan umur dua minggu dibagi dua kelompok. Kelompok A terdiri dari 50 ekor ayam yang dibagi menjadi 10 subkelompok dengan masing-masing subkelompok terdiri dari lima ekor. Kelompok B terdiri dari 150 ekor yang dibagi menjadi 10 subkelompok dengan masing-masing subkelompok 15 ekor. Kelompok A merupakan kontrol, sedangkan kelompok B sebagai kelompok perlakuan yang diinokulasi dengan 100 000 ookista Eimeria tenella yang telah bersporulasi Pemeriksaan darah subkelompok A1 dan B1 dilakukan pada saat prainokulasi, A2 dan B2 pada hari kedua setela inokulasi, A3 dan B3 pada hari ketiga, A4 den B4 hari keempat, A5 dan B5 hari kelima, A6 dan B6 hari keenam, A7 dan B7 hari ketujuh, A8 dan B8 hari kedelapan, A9 dan B9 hari kesepuluh, sedangkan A10 dan B10 diperiksa pada hari kedua belas setelah inokulasi.
Keyword: Ookista eimeria tenella;

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