Judul: Studi Komunitas Makrozoobenthos sebagai Indikator Kualitas Perairan di Situ Malangnengah, Parung, Kabupaten Bogor, Jawa Barat
Abstrak: Penelitian ini bertujuan untuk mengetahui kondisi kualitas perairan Situ Malangnengah dari faktor fisika, kimia dan biologi (makrozoobenthos). Hasil yang diharapkan dari pengamatan ini adalah mampu menjawab tingkat pencemaran oleh bahan organik yang pada ujungnya dapat dilakukan berbagai upaya dalam mengembangkan potensi Situ Malangnengah dengan optimal secara berkelanjutan.
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Judul: Struktur komunitas makrozoobenthos sebagai indikator kualitas perairan situ Cigudeg, Kabupaten Bogor, Jawa Barat
Abstrak: Penelitian ini bertujuan untuk mempelajari struktur komunitas makrozoobenthos sebagai indikator biologis kualitas lingkungan perairan Situ Cigudeg, sehubungan dengan adanya masukan bahan pencemar dari kegiatan di sekitar situ. Penelitian ini dilaksanakan pada bulan November hingga Desember 1998, bertempat di Situ Cigudeg, Kecamatan Cigudeg, Kabupaten Bogor. Jumlah stasiun pengamatan sebanyak enam stasiun, yaitu Stasiun 1, 2 dan 3 di daerah inlet, Stasiun 4 dan 5 di daerah tengah situ dan Stasiun 6 di daerah outlet. Contoh makrozoobenthos diambil dengan menggunakan alat Petersen grab, sedangkan contoh air dengan Kemmerer water sampler. Parameter fisika dan kimia perairan yang diukur meliputi suhu, kedalaman, kecepatan arus, pH, dan oksigen terlarut (DO) yang diukur langsung di lapangan (in situ). Sedangkan yang diukur di laboratorium meliputi kekeruhan, muatan padatan tersuspensi (TSS), kebutuhan oksigen kimiawi (COD), ammonia, serta analisis kandungan C-organik dan tekstur substrat. Analisis data makrozoobenthos dilakukan dengan menghitung komposisi jenis, keanekaragaman, keseragaman, dominansi, pola sebaran jenis, serta analisis nodul untuk melihat preferensi makrozoobenthos terhadap habitatnya. Hasil pengamatan terhadap komunitas makrozoobenthos diperoleh sebanyak delapan jenis makrozoobenthos yang tergolong dua filum yaitu Mollusca dan Annelida. Enam jenis yang termasuk filum Mollusca yaitu Thiara, Bellamya, Pomacea, Melanoides, Gyraulus dan Physa. Sedangkan dua jenis yang termasuk filum Annelida yaitu Branchiura dan Tubifex. Nilai indeks keanekaragaman jenis makrozoobenthos (H') di Situ Cigudeg tergolong rendah yaitu berkisar antara 0-1,409. Kecuali di Stasiun 5 (bagian tengah situ), nilai indeks keseragaman (E) tergolong rendah juga yaitu berkisar antara 0 0,377 yang menunjukkan adanya jenis yang mendominasi. Hal ini terlihat dari nilai...
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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