Judul: Pecemaran insektisida pada tiga species burung air di areal persawahan sukamandi, Subang, Jawa Barat
Abstrak: Peningkatan penggunaan insektisida di areal persawahan yang termasuk dalam program intensifikasi pertanian secara langsung maupun tidak langsung akakn membahayakan lingkungan dan mengancam kelestarian burung air, mengingat areal persawahan selain sebagai lahan penghasil pangan bagi manusia, juga merupakan habitat burung air. Dampak negatif langsung penggunaan insektisida terhadap burung air adalah terjadinya kematian saat penyemprotan, sedangkan dampak tidak langsung berupa peracunan terhadap rantai makanan, bioakumulasi, biomagnifikasi dan gangguan reproduksi.
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Judul: Evaluasi Lahan Basah sebagai Feeding Ground Burung Air Wilayah Indramayu dan Cirebon Utara
Abstrak: Salah satu kawasan lahan basah yang sering dijadikan habitat burung air di Indonesia adalah di sepanjang pesisir pantai utara Pulau Jawa. Wilayah muara Sungai Cimanuk Indramayu beserta kawasan pantainya menurut Musfari (1992) merupakan salah satu habitat penting bagi banyak jenis burung air. Kawasan ini tidak luput dari aktifitas manusia seperti pengembangan kawasan tambak, industri serta pemukiman yang dapat mengancam kelestarian burung air (Widodo eta/., 1996). Untuk menunjang upaya pelestarian burung air tersebut perlu diadakan penelitian mengenai habitat burung air. Salah satunya adalah identifikasi kawasan yang dijadikan areal makan Veedinggrour~d) di wilayah jelajah burung air.
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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