Judul: Performa Komunikasi Resiko dalam Upaya Penanganan dan Pengendalian Avian Influenza (Kasus Penanganan dan Pengendalian Avian Influenza di Kabupaten Tangerang - Banten)
Abstrak: Kasus flu burung yang terjadi pada manusia hingga September 2008 telah mencapai 143 kasus positif (confirm) dengan 112 kasus meninggal. Dikhawatirkan dengan terus meningkatnya kasus kematian pada manusia akan terjadi pandemi flu burung di Indonesia seperti yang terjadi pada tahun 1918, jutaan orang di belahan dunia meninggal akibat pandemi flu burung (US Department of Health & Human Services 2006). Kabupaten Tangerang telah ditetapkan oleh Pemerintah Republik Indonesia sebagai salah satu wilayah endemis. Avian Influenza. Data dari Dinas Pertanian dan Peternakan Kabupaten Tangerang hingga bulan April tahun 2009 terdapat 19 (sembilan belas) kecamatan dari 36 (tiga puluh enam) kecamatan yang positif kasus AI pada unggas. Selain itu, dari tahun 2005 hingga Maret 2009 tercatat bahwa terdapat 20 kasus konfirm AI dengan 18 orang meninggal dunia.
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Judul: Analisis Strategi Manajemen Risiko Kesehatan Hewan Pada Kasus Penyakit Avian Influenza di Kabupaten Bogor
Abstrak: Tujuan dari penelitian ini adalah mengidentifikasi, memetakan dan menganalisis manajemen risiko kesehatan hewan dan menentukan strategi prioritas manajemen risiko Flu Burung di Kabupaten Bogor. Metode ini menggunakan penilaian ahli untuk menentukan nilai risiko. Pemetaan risiko faktor menggunakan Failure Mode Effect Analysis(FMEA). Prioritas Strategi Manajemen Risiko menggunakan Analytical Hierarchy Process (AHP). Identifikasi faktor risiko tinggi adalah desinfeksi pengunjung di daerah peternakan, fluktuasi curah hujan, rendahnya pengetahuan peternak tentang cara beternak yang baik, dan rendahnya pemantauan sistem manajemen kesehatan dari pertanian ke perusahaan ritel. Prioritas faktor risiko strategi manajemen kesehatan adalah sumber daya manusia dan proses beternak. Prioritas aktor yang mempengaruhi strategi manajemen risiko kesehatan adalah perusahaan inti dan peternak. Prioritas tujuan manajemen risiko kesehatan adalah meningkatkan pendapatan. Prioritas Strategi manajemen risiko kesehatan adalah biosekuriti, vaksinasi dan lalu lintas pengendalian unggas
Keyword: Avian Influenza, biosekuriti, analisis risiko, manajemen risiko

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