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 Makrozoobentos Sebagai Indikator Kualitas Perairan Dl Sltu Tonjong, Kabupaten Bogor, Jawa Barat
Abstrak: Situ Tonjong (memiliki luas 7,65 ha & kedalaman rata-rata 2 m) terletak di Desa Tonjong Kecamatan Bojonggede, Kabupaten Bogor, Jawa Barat. Air Situ Tonjong berfungsi sebagai sumber irigasi untuk pesawahan dan kolam penkanan disekitarnya. Saat ini Situ Tonjong di kelola oleh Lembaga Ketahanan Masyarakat Desa (LKMD) yang mengatur kegiatan aktivitas pemancingan dan beberapa aktivitas pemanfaatan lainnya. Melihat kondisi perairan yang disekitarnya terdapat lahan-lahan perkebunan, lahan bekas persawahan, dan pemukimanserta beberapa aktivitas penangkapan ikan, maka diduga struktur komunitas makrozoobentos akan berbeda. Tuiuan dilakukannva oenelitian ini adalah untuk menentukan kualitas perairan dengan pendekakn biologi (makkzoobentos), dikaitkan dengan parameter fisika-kimia perairan. Penelitian ini dilaksanakan pada bulan Agustus sampai bulan Nopember 2000, dengan tiga stasiun daerah pengamatan yaitu : stasiun A (daerah dekat inlet dan sekitar perkebunan), stasiun B (daerah dekat outlet, pemukiman dan berbatasan dengan jalan raya) - ~ dan stasiun c (daerah dekat perkebunan dan pemukiman). Pengambilan contoh makrozoobentos dilakukan secara acak dan soasial, vaitu sebanvak . , 10 o. en-q ambilan (ulangan) pada masing-masing stasiun. ~en~ambilaconn toh kualitas air dilakukan secara spasial dan temporal, vaitu sebanyak empat kali .p en-g ukuran di stasiun A, B, dan C di dekat lapisan dasar perairan: Analisa kualitas air dilakukan di Lab. Kualitas Air Puslitbang Limnologi LIPI, sedangkan analisa makrozoobentos dilakukan di Lab. Biota Puslitbang LIP1 dan sebagian di Lab. Avertebrata Air Fakultas Perikanan dan llmu Kelautan IPB, serta untuk pengidentifikasian Gastropoda dibantu oleh staf Malakologi LIPI.
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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