Judul: Peran Komunitas Bakteri Dalam Pembentukan Rasa Pahit Pada Tempe : Analisis Mikrobiologi Dan Terminal Restriction Fragment Length Polymorphism (T-RFLP)
Abstrak: Tempe kedelai atau lebih dikenal dengan sebutan tempe merupakan produk pangan fermentasi tradisional masyarakat Indonesia. Cita rasa tempe sangat beragam, bahkan pada tempe tertentu ditemukan cita rasa yang tidak disenangi oleh konsumen seperti rasa pahit. Intensitas rasa pahit pada tempe dapat berbeda antar jenis tempe yang diproduksi pengrajin dan belum pernah dilaporkan faktor penyebabnya. Pada proses pembuatan tempe, mikroorganisme utama yang berperan adalah Rhizopus oligosporus, namun bakteri ditemukan juga dalam jumlah dan keragaman yang tinggi. Oleh sebab itu, penelitian ini bertujuan untuk mengkaji apakah komunitas bakteri berperan dalam pembentukan rasa pahit pada tempe. Hasil penelitian ini diharapkan bermanfaat untuk meningkatkan cita rasa tempe.
Keyword: fermented food, bitterness intensity, rhizophus oligosporus, Mucor sp., West Java

Judul: Analisis metagenom untuk pencirian komunitas bakteri dan fungi pada tempe
Abstrak: Tempe is an Indonesian traditional fermented food produced using Rhizopus as a starter culture. In practice, however, the starter culture as well as fermentation processes would involved a polymicrobial fermentation, which generated a unique tempe flavor and texture. This condition makes Indonesian tempe as one of the most complex fermented food, while at the same time would make it difficult to scale up tempe production with uniform quality and consistency. Because of complex microbial communities involved, cultureindependent methods or metagenomic analysis would be an essential tool to unravel this complex microbial fermentation. The aim of this study was to compare a number of tempe microbial communities based on Amplified Ribosomal Intergenic Sequence Analysis (ARISA). Fresh tempe samples were obtained from tempe producers in Java and Moluccas. 16S rRNA gene libraries and DNA sequencing were employed to analyze further the nature of microbial diversity in two selected tempe samples. The results of our study showed that different tempe producer possessed different Bacterial ARISA (BARISA) or fungi ARISA (FARISA) profiles. However, BARISA profiles were found to be more discriminative than FARISA, and therefore BARISA would be more useful for tempe genetic fingerprint or barcoding. Bacterial communities in two tempe samples (EMP and SDJD) were further investigated employing DNA sequence analysis of their 16S rRNA gene libraries. Sequences closely related to Klebsiella sp were found to be the majority among bacterial communities present in SDJD sample, while sequences closely related to Acetobacter sp. were found as predominant isolates in EMP samples. These significant differences in bacterial communities might reflect differences in tempe flavor or texture associated with their unique production or locality.
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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