Judul: Pengendalian Hayati Penyakit Hawar Daun Bakteri (HDB) Yang Menyerang Anakan Semai Acacia crassicarpa Cunn. ex Benth.
Abstrak: Sejak awal tahun 1970-an de/orestasi menjadi masalah penting di Indonesia. Pemanfaatan hutan terutama pemanenan kayu yang dilakukan secara berlcbihan tclah memberikan dampak berupa berkurangnya luasan kawasan hutan serta adanya kerusakan yang akhirnya dapat menurunkan fungsi hut:an secara keseluruhan.
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Judul: Biomatriconditioning, Perendaman Akar Atau Penyemprotan Tanaman Dengan Agens Hayati Untuk Mengendalikan Hawar Daun Bakteri, Meningkatkan Hasil Dan Mutu Benih Padi
Abstrak: Penyakit hawar daun bakteri (HDB) yang disebabkan oleh bakteri Xanthomonas oryzae pv. oryzae (Xoo), menurunkan produksi padi hingga 80%. Sifat patogen Xoo adalah terbawa benih, ditularkan melalui udara, tular tanah, bahkan tular air. Penelitian ini terdiri atas dua percobaan. Percobaan I bertujuan memperoleh konsentrasi agens hayati (Pseudomonas diminuta A6 + Bacillus subtilis 5/B) terbaik untuk perendaman akar bibit, yang efektif mengendalikan HDB, meningkatkan hasil dan mutu benih padi di rumah kaca. Percobaan I menggunakan rancangan lingkungan rancangan acak kelompok dan rancangan perlakuan petak terbagi. Petak utama adalah perlakuan benih dan anak petak adalah konsentrasi agens hayati untuk perendaman akar bibit. Hasil percobaan I menunjukkan, biomatriconditioning (matriconditioning dengan agens hayati P. diminuta A6 + B. subtilis 5/B 4.5 x 108 cfu mL-1) meningkatkan daya tumbuh, indeks vigor dan bobot kering bibit padi dibandingkan kontrol negatif. Biomatriconditioning juga meningkatkan tinggi tanaman, bobot kering tanaman, jumlah anakan per rumpun, jumlah anakan produktif per rumpun, dan jumlah gabah total per rumpun, serta menurunkan tingkat keparahan penyakit HDB. Perendaman akar dalam suspensi P. diminuta A6 dan B. subtilis 5/B 106 cfu mL-1 meningkatkan jumlah anakan produktif per rumpun. Perlakuan perendaman akar menurunkan tingkat keparahan penyakit HDB pada umur 91 HST. Biomatriconditioning dilanjutkan dengan perendaman akar dalam suspensi agens hayati 108 cfu mL-1 menurunkan populasi Xoo terbawa benih dibandingkan kontrol (benih dengan Xoo tanpa perlakuan benih tanpa perendaman akar bibit). Percobaan II bertujuan memperoleh konsentrasi agens hayati filosfir F112 terbaik untuk penyemprotan tanaman, yang efektif mengendalikan HDB, meningkatkan hasil dan mutu benih padi di lapangan. Percobaan II menggunakan rancangan lingkungan rancangan acak kelompok dan rancangan perlakuan petak terbagi. Petak utama adalah perlakuan benih dan anak petak adalah konsentrasi agens hayati untuk penyemprotan tanaman. Hasil percobaan II menunjukkan, biomatriconditioning meningkatkan bobot kering bibit umur 21 HST dibandingkan kontrol negatif. Biomatriconditioning mengurangi keparahan penyakit HDB pada 72 HST, meningkatkan bobot gabah bernas per rumpun, dan viabilitas benih hasil panen. Penyemprotan tanaman dengan F112 108 cfu mL-1 menurunkan keparahan penyakit HDB 72 HST dibandingkan kontrol tanpa penyemprotan maupun penyemprotan dengan bakterisida (streptomisin 0.1%), meningkatkan jumlah anakan produktif, bobot gabah panen, dan viabilitas benih hasil panen dibandingkan kontrol tanpa penyemprotan.
Keyword: Bacillus subtilis, bakteri filosfir, Pseudomonas diminuta, rizobakteri, Xanthomonas oryzae pv. oryzae

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