Judul: Studi kualitas lingkungan fisika dan kimia perairan Teluk Banten Kabupaten Serang
Abstrak: Perairan Teluk Banten merupakan salah satu wilayah pesisir yang terdapat berbagai aktivitas dan kepentingan disana. Pada kawasan ini terdapat industri pariwisata di pantai Salira dan cagar alam P. Dua, industri dasar dan aneka industri di Bojonegara, sarana pelabuhan perikanan di Karangantu, usaha perikanan tambak, dan beberapa tempat se- bagai daerah penangkapan ikan bagi nelayan setempat. Berbagai kegiatan tersebut telah menghasilkan, limbah yang dibuang ke dalam perairan. Sebagai akibatnya akan mempengaruhi keadaan dan kualitas perairan tersebut. Ber- anjak dari hal tersebut penelitian ini bertujuan untuk me- ngetahui penyebaran horisontal dan vertikal beberapa para- meter fisika dan kimia perairan; dan mengkaji kondisi kualitas perairan dan tingkat pencemaran Teluk Banten. Penelitian dilakukan di perairan Teluk Banten pada bulan Nopember 1991. Parameter fisika yang diamati: suhu, kedalaman, kekeruhan, arus, daya hantar listrik, kecerahan, pasang surut, muatan padatan (tersuspensi dan terlarut). Parameter kimia yang diamati pH, salinitas, oksigen ter- larut, amonia, nitrat, fosfat, silikat, hidrokarbon minyak
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Judul: Kualitas Perairan Dan Hubungannva Dengan Struktur Komunitas Plankton Di Lokasi Buangan Limbah Industri, Perairan Bojonegara, Teluk Santen.
Abstrak: Penelitian ini bertujuan untuk mengetahui kualitas perairan di sekitar lokasi buangan limbah industri yang dinilai berdasarkan beberapa parameter fisika, kimiawi dan struktur komunitas plankton, serta mengkaji hubungan diantara parameter tersebut. Penelitian dilaksanakan pada bulan September dan Oktober 2002 dengan mengambil lokasi di Perairan Bojonegoro, Teluk Banten, Kabupaten Serang, Propinsi Santen. Pengukuran parameter dan pengambilan contoh air dilakukan sebanyak 2 tahap pada saat perairan surut, vaitu tanggal 1 September 2002 dan 6 Oktober 2002. Parameter yang diukur meliputi parameter fisika (kedalaman, suhu, arus, kecerahan, kekeruhan, padatan tersuspensi), kimiawi (pH, salinitas, DO, BODs, COD, nltrat , ortofosfat, silikat) dan biologi (fitoplankton, zooplankton).
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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