Judul: Pengaruh kegiatan pengolahan minyak terhadap kondisi kualitas air dan keragaman makrozoobenthos di perairan Dumai
Abstrak: Karya Ilmiah ini merupakan hasil penelitian yang dilakukan penulis dari tanggal 11 Februari hingga 11 April 1988. Lokasi penelitian di sekitar perairan pantai Selat Rupat, Kota Administratif Dumai, Kabupaten Bengkalis, Propinsi Riau. Penelitian ini bertujuan untuk mempelajari pengaruh limbah industri pengolahan minyak terhadap kondisi kualitas air dan keragaman makrozoobenthos. Jumlah stasiun penelitian terdiri dari 3 perairan yaitu , perairan di inlet kilang, outlet kilang, dan perairan Tanjung Palas. Analisa kualitas air dilakukan di laboratorium Pertamina Unit Pengolahan II Dumai. Pengambilan organisme makrozoobenthos dilakukan di perairan sekitar kilang, dan Tanjung Palas, dengan menggunakan metoda transek. Biota yang diperoleh diawetkan dengan menggunakan larutan formalin 4%, selanjutnya diidentifikasi lokasi penelitian dan sebagian lagi diidentifikasi di di Museum Zoologi Bogor. Tekstur substrat perairan dianalisa di laboratorium Departemen Ilmu-ilmu Tanah, Fakultas tanian, IPB.
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Judul: Struktur komunitas makrozoobenthos di Perairan Kanal Duri, Duri Kabupaten Bengkalis, Propinsi Riau
Abstrak: Penelitian ini bertujuan untuk melihat struktur komunitas makrozoobenthos di perairan kanal Duri, di daerah pemboran minyak bumi dengan mengkaji: 1. Faktor-faktor lingkungan yang banyak mempengaruhi keberadaan makrozoobenthos yang meliputi kualitas air dan substrat. University 2 . Komposisi jenis, Kepadatan jenis, Keanekaragaman jenis, Keseragaman jenis, Dominansi dan pola penyebaran jenis makrozoobenthos. 3. Penggunaan analisa Nodul untuk mengetahui preferensi makrozoobenthos terhadap habitatnya. Penelitian ini dilakukan pada bulan Juli 1998. Stasiun penelitian ditentukan berdasarkan metode pengambilan contoh sistematik (melihat daerah-daerah khusus). Lokasi penelitian terdiri dari empat stasiun, dan di tiap stasiun ditentukan tiga sub stasiun. Analisa struktur komunitas makrozoobenthos meliputi kepadatan jenis, keanekaragaman, keseragaman, dominansi, pola sebaran jenis dan analisa Nodul untuk melihat keberadaan makrozoobenthos di perairan. Parameter fisika-kimia kualitas air yang diukur adalah suhu, kecerahan, kedalaman, padatan tersuspensi (TSS), kecepatan arus, kekeruhan, oksigen terlarut (DO), pH, BOD, COD. Sedangkan parameter fisika-kimia substrat yang diukur adalah tekstur substrat, kandungan C-organik dan kandungan minyak. Suhu yang terukur selama penelitian antara 27-31°C, kecerahan perairan antara 30-57 cm, padatan tersuspensi antara 1,68-363,2 mg/l, kecepatan arus antara 0,179-0,514 m/dt, kandungan oksigen terlarut antara 2,4-6,30 mg/l, nilai kekeruhan antara 7-61 NTU, nilai pH yang terukur antara 4,45-6,03, nilai BOD antara 15,25-31,28 mg/l dan nilai COD-nya antara 48,77-98,78 mg/l. Secara umum kualitas air di daerah penelitian sudah terganggu. Sedangkan tipe substrat pada daerah penelitian adalah lempung, lempung berdebu, liat berdebu. ...
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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