Judul: Respons Penciuman Ikan Kerapu Macan (Epinephelus fuscoguttatus) terhadap Umpan Buatan
Abstrak: Kerapu macan (Epinephelus fuscoguttatus) umumnya ditangkap dengan menggunakan bubu, pancing, tombak, bahan peledak, dan bahan kimia beracun (potasium sianida). Kedua cara penangkapan yang disebutkan terakhir merupakan cara yang efektif, namun menimbulkan dampak yang merugikan terhadap kelestarian ekosistem terumbu karang dan sumberdaya ikan. Bubu termasuk kedalam jenis perangkap (trap) (Brandt, 1984) yang sering digunakan oleh nelayan untuk menangkap ikan karang. Menurut Subani dan Barus (1989), umpan merupakan salah satu faktor penting untuk menunjang keberhasilan suatu operasi penangkapan ikan dengan bubu dan pancing. Umpan digunakan dalam pengoperasian bubu berfungsi sebagai pemikat (attractor) dengan tujuan agar ikan karang yang sifatnya bersembunyi pada terumbu karang dapat keluar dan tertarik untuk masuk ke dalam bubu. Efektivitas umpan ditentukan oleh sifat fisik dan kimiawi yang dimilikinya agar dapat memberikan respons terhadap ikan-ikan tertentu.
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Judul: Studi Tingkah Laku Pelolosan Kerapu Macan (Epineplte/Usjuscoguttatus) Pada Bubu Yang Dilengkapi Dengan Celah Pelolosan (Escaping Gaps)
Abstrak: Bubu merupakan salah satu alat tangkap yang bersifat pasif dan digunakan untuk menangkap ikan karang, salah satunya adalah kerapu macan (Epinephelus fuscoguttatus). Bubu mempunyai pintu masuk berbentuk corong yang memungkinkan ikan mudah masuk ke dalam bubu tetapi sulit keluar (non-return device). Disamping itu, Lubu juga memiliki dinding dengan ukuran mata yang relatifkecil, khususnya untuk jenis bubu kawat dan bubu plastik, sehingga ikan muda yang belurn layak tangkap dan memiliki ukuran tubuh lebih besar dari ukuran mata dinding bubu akan sulit untuk meloloskan diri. Oleh karena itu perIu dibuat suatu celah pelolosan (escaping gap) pada bubu agar ikan tersebut dapat lolos dengan mudah tanpa terIuka. Tingkah laku ikan untuk meloloskan diri melalui celah pelolosan ini sangat berkaitan erat dengan bentuk dan ketinggian celah pelolosan dari dasar bubu.
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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