Judul: Uji Kapasitas Kijing Taiwan (Anodonta woodiana Lea) dalam menurunkan Kadar Polutan Pestisida Karbaril Pada Perairan Tawar
Abstrak: Uji kemampuan Kijing Taiwan 5 dan 10 ekor dalam menurunkan kaar pestisida kabari, sebesar 22ppm di dalam perairan tawar, Analisis dilakukan setiap pekan 28 hari dengan metode Kromatografi Gas. Hasil penelitian menunjjukkan bahwa pestisida karbaril dalam perairan menurun sejak 0-7 hari, untuk setiap kelompok.
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Judul: Uji kapasitas kijing Taiwan (Anodonta wooiana Lea) dalam menurunkan kadar endosulfan di Perairan Tawar
Abstrak: Pencemaran pestisida di perairan telah menimbulkan kematian pada ikan atau biota air lainnya. Kijing taiwan sebagai hewan air tawar dengan sifat hidup statis dan cara makan filter feeder telah di usahakan untuk membantu pengendalian/penurunan kadar polutan di perairan. Dalam penelitian ini akan dilihat pengaruh penambahan kij ing dengan jumlah yang berbeda ke dalam perairan yang tercemar terhadap penurunan kadar endosulfan. Penelitian ini dibagi menjadi tiga kelompok yaitu kelompok kontrol (air + endosulfan tanpa kijing), kelompok I (air + endosulfan dengan 5 kijing) dan kelompok II (air + endosulfan dengan 10 kijing), diamati selama 28 hari. Uji toksisitas akut dilakukan untuk mengetahui LC50 endosulfan dan konsentrasi yang akan digunakan tanpa menimbulkan kematian pada kijing selama 28 hari. LC50 endosulfan berdasarkan hasil analisis probit adalah 295.46 ppm sedangkan konsentrasi yang digunakan berdasarkan hasil uji toksisitas akut adalah 8 ppm. Kadar endosulfan baik pada kontrol maupun perlakuan (kelompok [ dan kelompok [I) mengalami penurunan. Penurunan pada kelompok I dan kelompok ll lebih tinggi dibandingkan kontrol, ha! ini disebabkan masing-masing kijing mengakumulasi endosulfan melalui saluran masuk air bersama­sama makanannya. Pada kelompok I, selama 28 hari kijing mampu menurunkan kadar endosulfan sampai 0,44 ppm, sedangkan pada kelompok [I kij ing mampu menurunkan kadar endosulfan sampai 0,24 ppm dari kadar awal 8 ppm. Berdasarkan analisis ragam, penurunan kadar residu endosulfan dalam air yang diberi kijing berbeda nyata terhadap kontrol (tanpa kijing) mulai pada hari ke-7 sampai hari ke-28 sedangkan penurunan kadar residu endosulfan pada 5 kijing berbeda nyata dengan 10 kijing pada hari ke-7 dan hari ke-14 tetapi tidak berbeda nyata pada hari ke-21 dan hari ke-28.
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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