Judul: Pengaruh Pemberian Ekstrak Daun Kemuning (Murraya paniculata (L.) Jack) terhadap Performa dan Kualitas Fisik Telur Puyuh Persilangan “Malon”.
Abstrak: Penelitian bertujuan melihat pengaruh dari ekstrak daun kemuning (Murraya paniculata (L.) Jack) yang ditambahkan dalam air minum terhadap performa dan kualitas fisik telur puyuh. Penelitian ini menggunakan 240 ekor puyuh persilangan “Malon” betina berumur 24 minggu selama 34 hari dengan ransum komersial berbentuk crumble dengan protein kasar 20.01 % dan energi bruto 3703 kkal kg-1. Daun kemuning diekstrak dengan menggunakan juicer. Rancangan acak lengkap (RAL) dengan empat perlakuan dan dua ulangan digunakan dalam peneilitian ini, perlakuan terdiri dari P0 = air minum tanpa pemberian ekstrak daun kemuning, P1 = pemberian 3% ekstrak daun kemuning dalam air minum, P2 = pemberian 5% ekstrak daun kemuning dalam air minum dan P3 = pemberian 7% ekstrak daun kemuning dalam air minum. Variabel yang digunakan untuk mengukur performa dan kualitas fisik telur yaitu konsumsi ransum, produksi telur, bobot telur, konversi ransum, konsumsi air minum, mortalitas, indeks telur, persentase bobot kuning telur, persentase putih telur, persentase kerabang telur, skor warna kuning telur serta tebal kerabang telur. Hasil penelitian ini menunjukkan bahwa pemberian ekstrak daun kemuning dalam air minum dengan taraf 3% hingga 7% tidak mempengaruhi secara signifikan performa dan kualitas fisik telur.
Keyword: Murraya paniculata (L.) Jack, performa, puyuh petelur persilangan “Malon”

Judul: Profil Lipid Darah dan Organ Dalam Puyuh Petelur Persilangan “Malon” Diberi Ekstrak Daun Kemuning (Murraya paniculata (L.) Jack) dalam Air Minum.
Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh pemberian ekstrak daun kemuning (Murraya paniculata (L.) Jack) melalui air minum terhadap profil lipid darah dan organ dalam puyuh petelur. Penelitian ini menggunakan 240 ekor puyuh persilangan “Malon” betina berumur 24 minggu. Puyuh dipelihara selama 5 minggu dan diberi pakan komersial yang mengandung protein kasar 20.01% dan energi bruto 3703 kkal kg-1. Ekstrak daun kemuning menggunakan air dan alat juicer. Rancangan percobaan menggunakan Rancangan Acak Lengkap (RAL) dengan 4 perlakuan dan 2 ulangan. Jumlah sampel untuk analisis profil lipid darah menggunakan puyuh sebanyak 2 ekor tiap ulangan. Perlakuan yang diberikan yaitu P0 = kontrol dan penambahan ekstrak daun kemuning dalam air minum sebanyak 3% (P1), 5% (P2), dan 7% (P3). Data profil lipid darah dianalisis menggunakan analisa deskriptif dan data organ dalam dianalisis dengan sidik ragam ANOVA. Hasil penelitian menunjukkan bahwa penambahan ekstrak daun kemuning (Murraya paniculata (L.) Jack) dalam air minum hingga 7% tidak mempengaruhi profil lipid darah dan organ dalam puyuh petelur.
Keyword: Murraya paniculata (L.) Jack, organ dalam, profil lipid darah, puyuh petelur persilangan “Malon”

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