Judul: Pengaruh Tingkat Pemberian Makanan Buatan terhadap Pertumbuhan dan Produksi Ikan Mas (Cyprinus carpio Linn) yang dipelihara di dalam Drum
Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh tingkat pemberian makanan buatan terhadap pertumbuhan dan produksi ikan mas, yang dipelihara di dalam drum. Percobaan di lakukan di perkolaman Shidora, Ciampea Udik, Kabupaten Bogor selama 8 minggu yaitu dari tanggal 30 September sampai 25 Nopember 1383. Wadah yang digunakan untuk penelitian adalah drum plastik berbentuk silinder dengan volume total 125 1iter sebanyak 12 buah. Setiap drum diisi air sebanyak 100 liter, dan debit air dipertahankan sebesar 10 liter permenit untuk setiap drum. Air yang digunakan berasal dari saluran irigasi. Pembersihan wadah dilakukan sekali seminggu.
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Judul: Pengaruh Pemberian Jumlah Makanan yang Berbeda terhadap Pertumbuhan Ikan Mas (Cyprinus carpio Linn.)
Abstrak: Bagi usaha pengembangan budidaya ikan penelitian mengenai komposisi makanan buatan, pembuatannya maupun cara pemberiannya kepada ikan sangat diperlukan. Dalam hubungannya dengan efisiensi usaha budidaya secara ekonomis, salah satu aspek penting adalah jumlah makanan harian yang harus diberikan kepada ikan. Penelitian yang telah dilaksanakan penulis dari tanggal 1 Juni sampai dengan 26 Juli 1983, bertempat di Laboratorium Gizi dan Teknologi Makanan Ikan, Salai Penelitian perikanan Darat (BPPD), Jalan Sempur No. 1 Bogor. Tnjuan penelitian adalah untuk mengetahui jumlah makanan harian yang tepat yang diperlukan ikan mas berukuran berat rata-rata 40 gram, agar tercapai pertumbuhan yang optimal 1).
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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