Judul: Studi Beberapa Aspek Biologi Kepiting Pasir di Kecamatan Buluspesantren, Kabupaten Kebumen
Abstrak: Kepiting pasir dikenal oleh masyarakat Kebumen dengan sebutan yutuk dengan common name yaitu mole crab atau sand crab. Kepiting pasir merupakan salah satu jajanan khas pantai di Kebumen yang dikonsumsi dalam bentuk rempeyek. Selain dimanfaatkan sebagai sumber protein, kepiting pasir juga dapat dimanfaatkan sebagai indikator pencemaran (Boere et al. 2011). Studi mengenai kepiting pasir di dunia sudah banyak dilakukan, akan tetapi di Indonesia hanya penelitian mengenai kandungan omega 6 yang dilakukan oleh Mursyidin (2007), sehingga data dan informasi mengenai kepiting pasir masih minim. Oleh karena itu, perlu dilakukan penelitian mengenai studi beberapa aspek biologi kepiting pasir dari jenis Emerita emeritus dan Hippa ovalis yang meliputi aspek pertumbuhan, distribusi frekuensi panjang karapas, nisbah kelamin, dan aspek reproduksi yang meliputi fekunditas dan stadia telur, sehingga dapat menjadi input untuk pengelolaan sumberdaya perikanan kepiting pasir.
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Judul: Estimasi Produktivitas Sekunder Kepiting Pasir Emerita emeritus dan Hippa ovalis Pada Maret sampai Mei 2012 di Pantai Berpasir, Kabupaten Kebumen, Jawa Tengah
Abstrak: Kepiting pasir merupakan hewan krustasea yang dapat ditemui di daerah intertidal sepanjang pesisir pantai selatan Kebumen. Kepiting pasir mempunyai peran penting dalam rantai makanan yaitu sebagai pemakan suspensi. Selain itu, kepiting pasir juga merupakan penyedia makanan untuk konsumer pada tingkat trofik yang lebih tinggi. Bagi masyarakat pesisir Kebumen, kepiting pasir banyak dimanfaatkan sebagai salah satu sumber penghasilan. Penelitian ini bertujuan untuk mengestimasi produktivitas sekunder yang dihasilkan oleh kepiting pasir Emerita emeritus dan Hippa ovalis. Penelitian dilaksanakan pada Maret sampai Mei 2012 di pantai berpasir, Kabupaten Kebumen, Jawa Tengah dengan interval pengambilan sampel satu bulan sekali. Analisis panjang dan bobot dilakukan di Laboratorium Biologi Mikro I, Departemen Manajemen Sumberdaya Perairan, Institut Pertanian Bogor. Analisis data yang dilakukan adalah penentuan sebaran frekuensi panjang dan estimasi produktivitas sekunder menggunakan metode non-kohort (sizefrequency).
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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