Judul: Produksi dan Inaktivitas In Vitro Toksin Isolat Corynespora cassiicola (Berk.&Curt.) Wei Asal Daun Karet
Abstrak: Penyakit Gugur Daun Corynespora pada tanaman karet yang disebabkan oleh Corynespora cassiicola [Berk. & Curt.] Wei telah menjadi ancaman bagi produksi karet di Indonesia. Cendawan patogenik tersebut menghasilkan toksin yang dinamakan cassiicoloa yang berperan penting dalam patogenisitasnya. Hingga saat ini masih belum diketahui strategi pengendalian yang efektif dan efisien untuk mencegah epidemi penyakit tersebut
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Judul: Inventarisasi dan identifikasi cendawan antagonis terhadap Corynespora cassiicola (Berk dan Curt.) Wei penyebab penyakit gugur daun tanaman karet (Hevea brasiliensis Muell. Arg.)
Abstrak: Penyakit gugur daun Corynespora muncul pada awal 1985 sebagai penyakit yang meresahkan para pekebun karet di Jawa barat, Jawa Tengah dan Sumatera Utara. Penelitian pengendalian secara kimiawi dan budidaya untuk penyakit ini telah banyak dilaksanakan, sedang untuk pengendalian biologi belum dilakukan. Oleh karena itu dilakukan penelitian yang bertujuan untuk menginventarisasi dan mengidentifikasi cendawan yang dapat bersifat antagonis terhadap Corynespora cassiicola penyebab penyakit gugur daun karet. Kegiatan penelitian ini dilaksanakan di Laboratorium Cendawan Patogen Tumbuhan Jurusan Hama dan Penyakit Tumbuhan, Fakultas Pertanian, Institut Pertanian Bogor, dimuali dari bulan Agustus sampai bulan Desember 1989. Dalam penelitian ini dilaksanakan isolasi cendawan dari daun karet dengan metode pencucian yaitu dengan memasukkan potongan daun karet yang telah dibersihkan ke dalam air destilata steril dan menumbuhkan suspensi tersebut pada media PDA. Organisme yang tumbuh kemudian diuji dengan uji antagonisme metode berganda. Parameter yang diamati ialah diameter koloni cendawan yang diduga antagonis dan C. cassiicola, juga terbentuk atau tidaknya zone penghambatan serta adanya hiperparasitisme.
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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