Judul: Isolasi Enterobacter cloacae Penghasil 2,3-Butanediol dari Tempe.
Abstrak: Senyawa 2,3-butanediol (2,3-BD) digunakan diberbagai industri seperti industri kosmetik, makanan, bahan bakar dan polimer.Maka dari itu, studi ini adalah yang pertama untuk mengisolasi bakteri penghasil 2,3-BDdari tempe yang dapat menggunakan gliserol karena umumnya bakteri yang memproduksi 2,3-BD menggunakan glukosa dan sukrosa sebagai sumber karbon.Berlimpahnya gliserol mentah menyebabkan pengembangan bahan organik ini sebagai substrat untuk industri mikrobiologi seperti 1,3-propanodiol (1,3-PD) dan 2,3-BD. Penelitian ini mendapatkan isolat penghasil 2,3-BD dari tempe yang telah diidentifikasi melalui sekuen 16S rRNA.Isolat 20, 25, dan 70 adalah Enterobacter cloacaedengan 100%kemiripan isolat dengan pembanding di GenBank.Konsentrasi 2,3-BD yang dihasilkan setelah 48 jam dari isolat 20, 25 dan 70 secara berturut-turut yaitu 3,703 gL-1, 5,201gL-1, dan 4,385gL-1 pada kondisi aerobik.
Keyword: 2,3-butanediol, tempe, Enterobacter cloacae

Judul: Biosintesis 1,3-Propanadiol Dari Gliserol (Hasil Samping Biodiesel) Oleh Bakteri Enterobacter aerogenes
Abstrak: Penelitian ini bertujuan untuk menghasilkan senyawa 1,3-propanadiol melalui fermentasi gliserol sebagai hasil samping produksi biodiesel oleh bakteri mutan Enterobacter aerogenes AD-H43 dan membandingkan dua metode separasi (distilasi pada tekanan udara normal dan distilasi vakum) 1,3-propanadiol dari broth fermentasi. Penelitian dilakukan di Laboratorium Teknologi Bioindustri BPPT, Puspiptek Serpong, Tangerang dan Laboratorium Terpadu UIN Syarif Hidayatullah Jakarta selama 6 bulan (Juli-Desember 2007). Penelitian diawali dengan penentuan bakteri yang digunakan dan terbukti bahwa mutan Enterobacter aerogenes AD-H43 memproduksi 1,3-propanadiol yang lebih tinggi (31,13%) dibandingkan dengan Enterobacter aerogenes AY-2 (26,06%). Limbah biodiesel sebagai substrat gliserol dipurifikasi dahulu sehingga konsentrasinya sebesar 17,5 g/l. Fermentasi dilakukan mulai dari pembuatan kultur kerja 50 ml, pra-pra kultur 35 ml, pra kultur 350 ml sampai kultur utama (main culture) 3500 ml. Fermentasi dilakukan pada fermentor 6 liter (T=37 oC dan pH 6,8) selama 20 jam. Pengukuran terhadap pertumbuhan bakteri (OD=680 nm dan pH) diamati setiap 4 jam. Hasil fermentasi kemudian disentrifugasi, filtratnya diseparasi dengan dua metode, yaitu distilasi pada tekanan udara normal (T=105 oC, 190 oC) dan distilasi vakum menggunakan alat rotari evaporator (T= 40 oC). Proses separasi dengan dua metode kemudian dianalisis menggunakan kromatografi gas-spektrometri massa (GC-MS).
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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