Judul: Pengaruh Proses Pengeringan Terhadap Aktivitas Antibakteri Ekstrak Rimpang Temulawak (Curcuma xanthorrhiza Roxb.)
Abstrak: Temulawak (Curcuma xanthorrhiza Roxb.) merupakan salah satujenis tanaman yang mempunyai arti penting dalam obat-obatan tradisional. Dari hasil penelitian dunia kedokteran modern. diketailUi ballwa khasiat temulawak terutama disebabkan oleh dua kelompok kandungan kimia utamanya yaitu kurkuminoid dan minyak atsiri.
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Judul: Aktivitas antibakteri rimpang temulawak (Curcuma xanthorrhiza Roxb.)
Abstrak: Penelitian ini dilakukan untuk menguji hipotesis bahwa rimpang temulawak mempunyai aktivitas antibakteri dan menentukan KHTM (Konsentrasi Hambat Tumbuh Minimal). Rimpang temulawak diambil filtratnya kemudian dibagi tiga. Pertama langsung diuji sifat antibakterinya, yang kedua diotoklaf dan yang ketiga dikeringkan (dijadikan bubuk). Ketiga filtrat tersebut diujikan terhadap empat bakteri uji, menggunakan metode perforasi. Bakteri yang digunakan adalah bakteri Gram Positif, yaitu Bacillus subtilis dan Staphyloccoccus aureus, bakteri Gram Negatif, yaitu Escherichia coli dan Pseudomonas aeruginosa. Filtrat yang dikeringkan (bubuk) digunakan untuk menentukan KHTM. Konsentrasi bubuk yang menghasilkan hambatan terbesar digunakan untuk hitungan cawan (untuk mengetahui jumlah bakteri yang masih hidup) dan turbidimetri (kekeruhan). Uji fitokimia rimpang temulawak mengandung senyawa alkaloid. Aktivitas antibakteri filtrat rimpang temulawak yang tidak diotoklaf lebih tinggi dibandingkan yang diotoklaf. KHTM bakteri B. subtilis, S. aureus, E. coli dan P. aeruginosa berturut-turut adalah 2.5, 2.5, 2.5, dan 5 mg/mL. Konsentrasi yang menghasilkan hambatan maksimum berturut-turut pada 50, 20, 30, dan 20 mg/mL. Aktivitas antibakteri bubuk rimpang temulawak yang menghasilkan hambatan maksimum terhadap bakteri E. coli, P. aeruginosa dan B. subtilis belum memiliki aktivitas antibakteri yang sebanding dengan antibiotik ampisilin 100 µg/mL, besarnya zona hambat maksimum berturut-turut adalah 0.3, 0.25, dan 0.3 dari zona hambat antibiotik ampisilin 100 µg/mL. Tetapi pada konsentrasi bubuk 16 mg/mL terhadap bakteri Staphylococcus aureus, zona hambatnya sudah sebanding dengan ampisilin 100 µg/mL. Berarti bubuk rimpang temulawak dengan konsentrasi 16 mg/mL dapat digunakan sebagai antibiotik terhadap penyakit yang disebabkan oleh bakteri Staphylococcus aureus. Konsentrasi yang menghasilkan hambatan terbesar, jumlah bakteri dan ODnya menjadi menurun.
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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