Judul: Keanekaragaman Jenis Amfibi (Ordo Anura) di Kebun Raya Bogor
Abstrak: Penelitian ini bertujuan untuk mengetahui keanekaragaman jenis amfibi (ordo anura) serta mengetahui keterkaitaii keanekaragaman jenis atnfibi jordo aouraj dengan karakteristik habitat di Kebun Raya Bogor. Penelitian dilakukan pada beberapa lokasi yang rnendukung kehidupan amfibi di KRB pada bulan Maret-Juni dan November 2001. Metode yarlg digunakan dalam pengambilan data adalah metode lfi.srrolErrcorrrrler SII~I~yaCn)g' d ilakukan pada malam hari selama 2,s jam, sementara itu pengambilan data habitat (kondisi lingkungan dan kondisi lokasi) dilakukan pada siang hari. Habitat amfibi di Kebun Raya Rogor dibagi menjadi 2 habitat besar yaitu akuatik dan terestrial. Suhu udara di KRB pada saat pengamatan berlangsung berkisar antara 22,6 - 28,S°C sedangkar~k elambaban berkisar antara 71% - 92%. sementara itu suliu air berkisar antara 25 - 29'C Cuaca pada saat pengamatan berlangsung lebih sering mendung berangin dan kadang-kadang disertai gerirnis. Kisaran pH berdasarkan llasil pengamatan antara 5.5 - 6.0. sementara itu llasil pengukuran padatan total diperoleh kisaraan antara 40 - 56 mg/L dan hasil pengukuran kekemhan antara 0.12 - 0,64 NTU.
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Judul: Keanekaragaman Jenis Amfibi (ordo Anura) di Kampus IPB Darmaga, Bogor
Abstrak: Amfibi merupakan bagian dari Keanekaragaman hayati dan ekosistem daerah tropis yang bermanfaat secara ekologi dan ekonomi bagi manusia, namun keberadaan datanya masih kurang. Penelitian ini bertujuan untuk mengetahu jenis-jenis amfibi (Ordo Anura) yang ada pada beberapa lokasi di Kampus IPB Darmaga dan mengetahui kondisi habitat jenis-jenis yan di temukan tersebut
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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