Judul: Struktur Komunitas Makrozoobentos dan Keterkaitannya Dengan Karakteristik Sedimen di Perairan Muara Sungai Bantan Tengah, Bengkalis
Abstrak: Perairan muara sungai Bantan Tengah terletak di Pulau Bengkalis, Kabupaten Bengkalis, Propinsi Riau. Sungai Bantan Tengah merupakan salah satu sungai yang mengalir di Pulau Bengkalis. Di daerah muara sungai ini berkembang kegiatan pemeliharaan ikan dalam keramba jaring apung yang jumlahnya mencapai ratusan unit. Dengan bertambahnya jumlah ini dikuatirkan akan mem-berikan dampak terhadap kondisi lingkungan perairan ini di masa mendatang, yaitu berupa peningkatan pencemaran organik. Tujuan dari penelitian ini adalah untuk mengkaji struktur komunitas makrozoobentos sebagai indikator kondisi perairan dan menentukan keterkaitan antara struktur komunitas makrozoobentos dan karakteristik sedimen muara sungai Bantan Tengah. Hasil penelitian ini diharapkan dapat memperkaya informasi mengenai struktur makrozoobentos dan kondisi perairan serta tentang faktor-faktor yang mempengaruhi distribusi makrozoobentos. Penelitian ini dilakukan di perairan muara sungai Bantan Tengah yang mencakup 11 stasiun pengamatan. Penelitian dilaksanakan dari awal bulan Maret 1997 sampai akhir bulan Mei 1997. Karaktedstik fisika-kimia air yang diukur adalah kedalaman perairan, suhu, kecerahan, kecepatan arus, salinitas, oksigen terlarut, pH, nitrat dan ortofosfat. Sementara itu karakteristik sedimen dasar yang diukur adalah derajat keasaman (pl-I), redokspotensial (Eh), organik total, C- organik, fraksi sedimen (pasir, lumpur dan liat), nitrat dan ortofosfat. Parameter biologi yang diamati adalah struktur komunitas makrozoobentos. dst ...
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Judul: Struktur Komunitas Makrozoobentos dan Keterkaitannya dengan Kualitas Air di Perairan Teluk Banten
Abstrak: Tingginya aktivitas antropogenik di kawasan pesisir Teluk Banten berpotensi menurunkan kualitas perairan akibat masuknya bahan-bahan organik dan anorganik. Penurunan kualitas air tersebut akan berdampak terhadap kehidupan biota, salah satunya makrozoobentos. Penelitian ini bertujuan menganalisis struktur komunitas makrozoobentos dan keterkaitannya dengan kualitas air di Teluk Banten. Penelitian dilakukan selama enam bulan, sejak bulan September 2022 hingga Februari 2023 dengan enam titik stasiun pengamatan. Metode yang digunakan terdiri dari analisis kualitas air secara insitu dan eksitu berupa sampel makrozoobentos yang diambil menggunakan Ekman Grab, parameter kualitas air, dan substrat. Analisis data yang dilakukan terdiri dari kepadatan, keanekaragaman, keseragaman, dominansi, tipe substrat, analisis similaritas, dan analisis komponen utama. Makrozoobenthos yang diperoleh terdiri dari enam kelas, yaitu Bivalvia, Gastropoda, Polychaeta, Scapopoda, Malacostraca, dan Echinoidea. Kepadatan makrozoobentos tertinggi pada musim kemarau di bulan September. Indeks keanekaragaman yang diperoleh terkategori tinggi dengan keseragaman dan dominansi yang rendah. Kualitas air yang paling berpengaruh bagi makrozoobentos di Teluk Banten, yaitu DO dan suhu., The high anthropogenic activities in the coastal area of Banten Bay have potential to reduce water quality due to the load of organic and inorganic materials. The decrease in water quality will have an impact on biota life, one of which is macrozoobenthos. This study aims to analyze the structure of the macrozoobentos community and its relationship with water quality in Banten Bay. The study was conducted for six months, from September 2022 to February 2023 with six observation stations. The method used consists of in situ and ex situ water quality analysis in the form of macrozoobenthos samples taken usingEkman Grab, water quality parameters, and substrate. The data analysis carried out consisted of density, diversity, uniformity, dominance, substrate type, similarity analysis, and principal component analysis. The macrozoobenthos obtained consist of six classes, namely Bivalves, Gastropods, Polychaeta, Scapopoda, Malacostraca, and Echinoidea. The density of macrozoobenthos was highest at dry season in September. The diversity index is categorized as high with low uniformity and dominance. The most influential water quality for macrozoobentos in Banten Bay is DO and temperature.
Keyword: makrozoobentos di Teluk Banten, kualitas air, struktur komunitas, Teluk Banten

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