Judul: Uji Mikrob Antagonis Rhizosfer Terhadap Penyakit Rimpang Pada Tanaman Kencur (Kaemfaria galangan Linn.)
Abstrak: Prospek kencur di berbagai industri Indonesia utamanya jamu memiliki nilai pengembangan yang baik. Data statistik dari Kementerian Pertanian menunjukkan tahun 2012, 2013 dan 2014 hasil produksi kencur mengalami penurunan yang tinggi. Pengaruh terbesar penurunan hasil produksi kencur yaitu konversi lahan dan infeksi penyakit tanaman. Metode pengendalian yang aman, efektif dan murah diperlukan sebagai pengganti fungisida dalam pengendalian penyakit kencur. Penelitian ini bertujuan mendapatkan mikrob rhizosfer yang efektif dan berpotensi sebagai pengendalian patogen kencur. Metode penelitian meliputi isolasi cendawan dan bakteri, uji patogenisitas, uji antagonis, dan identifikasi. Hasil isolasi kencur sakit didapatkan tiga cendawan (Fusarium oxysporum, Fusarium solani dan Curvularia brachyspora) dan lima isolat bakteri (BB1, BB2, BB3, P1, dan P2) yang bersifat patogen dari hasil uji patogenisitas. Isolasi dari rhizosfer didapatkan dua cendawan (Penicillium sp. dan Chaetomium aureum) dan dua isolat bakteri (RRH6 dan R2) yang bersifat non patogen serta berpotensi mengendalikan penyakit kencur. Pada uji antagonis, potensi antagonis Penicillium sp. dan C. aureum ditunjukkan dengan cara antibiotik, lisis, parasitisme dan pembengkakan hifa sehingga mengakibatkan perkembangan hifa abnormal, tetapi kedua cendawan tidak memiliki kemampuan kompetisi ruang dan nutrisi. Potensi antagonis bakteri RRH6 dan R2 adalah menghasilkan senyawa bioaktif yang dapat menghambat pertumbuhan bakteri patogen. Berdasarkan identifikasi bakteri, semua isolat bakteri berjenis Gram negatif, berwarna merah, dan berbentuk kokus
Keyword: bakteri antagonis, bakteri patogen, C. aureum, C. brachyspora, Penicillium sp

Judul: Eksplorasi agens antagonis dari tanaman dan rihzoseir padi untuk menekan rhizoctonia solani Kuhn penyebab hawar pelepah padi
Abstrak: Penelitian ini bertujuan untuk mendapatkan mikroorganisme yang mampu berfungsi sebagai agens antagonis yang potensial terhadap Rhizoctonia solani penyebab hawar pelepah padi. Percobaan dilakukan di Laboratorium Mikologi Tumbuhan, Jurusan Hama dan Penyakit Tumbuhan, Fakultas Pertanian Institut Pertanian Bogor. Isolasi cendawan R. solani asal rhizosfir pertanaman padi sawah di Muara dilakukan dengan metode penanaman jaringan pangkal batang padi yang terinfeksi hawar pelepah dan metode penanaman sklerotia. Patogen R. solani berha- sil diisolasi dan mudah ditumbuhkan pada media PDA. Isolasi agens antagonis dilakukan dengan metode pengenceran baik pada media PDA yang diberi kloramfenikol 100 mg/liter maupun media Nutrient Agar. Media PDA digunakan untuk mengisolasi agens antagonis dari golongan cendawan dan media NA untuk mengisolasi agens antagonis dari golongan bakteri. ...
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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