Judul: Kajian Karakteristik Sifat Kualitatif dan Hematologis Ayam Cemani sebagai Upaya untuk Meningkatkan Kualitas Kemurnian
Abstrak: Ayam cemani merupakan ayam kedu hitam yang diseleksi warna hitam pada bulu dan jenggernya serta bentuk jengger tunggal bergerigi. Sampai saat ini, upaya untuk membentuk galur murni ayam lokal Indonesia dengan kualitas yang baik masih terbatas. Penelitian ini bertujuan mengkaji karakteristik kualitatif dan hematologis ayam cemani pada beberapa grade yang berbeda sebagai upaya untuk meningkatkan kualitas (kemurnian, status kesehatan, dan performa). Penelitian ini menggunakan 8 ekor ayam cemani jantan dan 14 ekor ayam cemani betina dari 3 grade yang berbeda (A super, A, dan B). Darah diambil melalui vena brachialis menggunakan spuit, kemudian dianalisis hematologisnya. Karakteristik sifat kualitatif ayam cemani meliputi warna lidah hitam, abu-abu dan kuning, warna kulit hitam, pola bulu hitam (E_), corak bulu polos (bb), kerlip bulu perak (S_), warna shank hitam (id), bentuk jengger single (pp), warna cuping hitam, dan warna iris mata cokelat. Tingginya nilai eritrosit berpengaruh terhadap intensitas warna hitam pada lidah ayam cemani. Perbedaan grade antara ayam cemani grade A super dengan grade A tidak berbeda nyata (P>0.05) pada semua komponen hematologis. Namun demikian hematokrit, jumlah leukosit dan MCV berbeda nyata pada ayam jantan grade A super dan betina grade A super.
Keyword: ayam cemani, grade kualitas, hematologis, jenis kelamin, karakteristik kualitatif

Judul: Cemani Chicken (Gallus gallus domesticus) Erythrocites Mass Indicator Profile
Abstrak: Ayam cemani diketahui sebagai salah satu ayam lokal Indonesia yang unik karena seluruh tubuh termasuk dagingnya berwarna hitam. Penelitian ini bertujuan membandingkan jumlah eritrosit, kadar hemoglobin, nilai hematokrit, indeks eritrosit, dan saturasi oksigen ayam cemani dengan ayam pedaging, ayam petelur, dan ayam kampung. Sampel darah diambil dari vena brachialis tiga ekor ayam cemani dengan bobot badan ± 800-1000 gram. Analisis indikator massa eritrosit ayam cemani menggunakan metode hemasitometer, hemoglobin Sahli, dan tabung mikrokapiler, dan veterinary pulse oxymeter. Hasil pemeriksaan rata-rata jumlah eritrosit 4.46 ± 0.22 (10^6 sel/mm3), kadar hemoglobin 10.17 ± 1.04, nilai hematokrit 25.87 ± 4.05, nilai MCV 57.75 ± 6.35, nilai MCH 22.81 ± 2.51, nilai MCHC 39.99 ± 7.86, dan saturasi oksigen 76%. Berdasarkan data hasil pemeriksaan, dapat disimpulkan jumlah eritrosit ayam cemani lebih tinggi dari ayam pedaging, petelur, dan kampung. Kadar hemoglobin ayam cemani sedikit lebih tinggi, sedangkan nilai hematokrit berada dalam rentang ayam pedaging, petelur, dan kampung. Nilai MCV dan MCH ayam cemani lebih rendah, tetapi nilai MCHC tidak jauh berbeda dari ketiga ayam pembanding. Saturasi oksigen ayam cemani tidak jauh berbeda dengan ketiga ayam lainnya.
Keyword: ayam cemani, eritrosit, hematokrit, hemoglobin, indeks eritrosit

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