Judul: Pengaruh Frekuensi Pemberian Pakan terhadap Pertumbuhan Benih Ikan Koan (Ctenopharyngodon idella C.V.)
Abstrak: Penelitian ini dilaksanakan di Instalasi Kolam Percobaan Balai Penelitian Perikanan Air TAwar, Cibalagung, Bogor dari bulan Maret sampai April 19889 untuk mengetahui pengaruh frekuensi pemberian pakan terhadap pertumbuhan maksimum benih ikan koan (Ctenopharyngodon idella C.V.). Ikan yang digunakan adalah benih ikan koan denganpanjang 3-5 cm dan bobot rata-rata 0,62 g dipelihara dengan padat penebaran 1 ekor per liter. Wadah berupa bak fiberglaas berbentuk persegi panjang, masing-masing diisi air sebanyak 15 liter. Pakan yang diberikan berupa tepung Indofeed sebanyak 11% dari bobot biomassa ikan setiap hari.
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Judul: Pengaruh Salinitas Terhadap Kelangsungan Hidup Dan Pertumbuhan Benih Ikan Koan (Ctenopharyngodon idella C.V)
Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh salinitas terhadap kelangsungan hidup dan pertumbuhan benih ikan koan berukuran panjang 5 -7 cm dengan bobot rata-rata individu 3,86 g. Sebagai penunjang diukur juga efisiensi pemberian pakan. Penelitian dilaksanakan dari pertengahan April sampai pertengahan Juni 1989 di Instalasi Kolam Percobaan, Balai Penelitian Perikanan Air Tawar, Cibalagung, Bogor. Percobaan ini menggunakan rancangan acak lengkap (RAL) dengan lima perlakuan masing-masing adalah salinitas 0, 3, 6, 9 dan 12/00. Setiap perlakuan diulang tiga kali. Padat penebaran ikan yang digunakan adalah satu ekor per liter atau 15 ekor per wadah. Benih tersebut diberi pakan buatan berbentuk tepung dengan kandungan protein sebesar 41,38%. Jumlah pakan yang diberikan adalah 5% dari biomass ikan, tiga kali dalam satu hari sama banyak, yaitu pada jam 08.00, 12.00 dan 17.00 WIB. Penyesuaian jumlah pakan dilakukan seminggu sekali setelah penimbangan ikan. Wadah yang digunakan adalah 15 akuarium kaca berukuran panjang 30 cm, lebar 30 cm dan tinggi 40 cm. Volume air di tiap akuarium adalah 15 1. Air dalam akuarium diaerasi.
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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