Judul: Kajian aktivitas antimikroba ekstrak kulit kayu mesoyi, Cryptocaria massoia terhadap bakteri patogen dan pembusuk pangan
Abstrak: Di Indonesia terdapat kira-kira 4000 jenis kayu dan dari jumlah tersebut masih banyak yang belum diketahui sifat dan kegunaannya, termasuk didalamnya adalah tanaman mesoyi (Cryptocaria massoia). Penelitian ini bertujuan untuk mengkaji aktivitas antimikroba pada kulit kayu mesoyi sebagai salah satu sumber daya alam khas Indonesia yang belum optimal pemanfaatannya. Dengan diketahui aktivitas antimikrobanya diharapkan penggunaan kulit kayu mesoyi dapat dikembangkan sebagai salah satu sumber antimikroba alami. Penelitian dibagi atas dua tahapan, yaitu penelitian pendahuluan dan penelitian lanjutan. Pada penelitian pendahuluan dilakukan persiapan kultur bakteri uji, proses ekstraksi, dan pengujian aktivitas antimikroba dengan metode uji difusi sumur. Pada penelitian lanjutan dilakukan penentuan nilai MIC dan uji fitokimia terhadap ekstrak kulit kayu mesoyi terpilih. Persiapan kultur bakteri uji dilakukan dengan metode hitungan cawan dan didapatkan bahwa pengenceran yang diperlukan adalah 10-3. Proses ekstraksi dilakukan dengan metode refluks dan destilasi uap. Proses ekstraksi dilakukan secara tunggal dengan pelarut air dan etanol, serta secara bertingkat dengan pelarut heksan, etil asetat, dan metanol. Rendemen ekstrak air, ekstrak etanol, minyak atsiri, ekstrak heksan, ekstrak etil asetat, dan ekstrak metanol kulit kayu mesoyi berturut-turut adalah 7.80% (w/w), 8.93% (w/w), 2.04% (w/v), 1.69% (w/w), 1.47% (w/w), dan 1.52% (w/w).
Keyword: aktivitas antimikroba

Judul: Antibacterial Activity of Meranti Bark Ethanol Extract Againts Staphylococcus aureus
Abstrak: Ekstrak kulit kayu meranti diketahui memiliki aktivitas antibakteri. Dalam penelitian ini, berbagai konsentrasi etanol, 50% (E50), 75% (E75), dan 100% (E100) digunakan sebagai pelarut untuk mengekstraksi kulit kayu menggunakan metode ekstraksi soxhlet. Hasil ekstrak ditentukan dan kemudian dilakukan uji aktivitas antibakteri terhadap S. aureus menggunakan metode difusi cakram. Kandungan fitokimia ditentukan secara kualitatif mengacu pada metode Harborne. Komposisi kimia ekstrak dengan aktivitas antibakteri tertinggi dianalisis dengan LC-MS dan dikonfirmasi dengan spektroskopi FTIR. Hasil penelitian menunjukkan bahwa rendemen ekstrak tertinggi diperoleh pada E75 (8,39%), diikuti oleh E50 (7,86%), dan E100 (6,58%). Ekstrak tersebut dapat menghambat pertumbuhan S. aureus pada kisaran sedang sampai kuat. Analisis fitokimia dan spektrum FTIR mengkonfirmasi adanya kandungan flavonoid, fenolhidrokuinon, tanin, saponin, dan triterpenoid dalam ekstrak. Analisis LC-MS menunjukkan adanya (+)-Nootkatone, aurantimide acetate, Vitisin C, Kievitone yang diduga berperan dalam aktivitas antibakteri terhadap S. aureus., Meranti bark extract has been known posses the antibacterial activity. In this study, various concentrations of ethanol, 50% (E50), 75% (E75), and 100% (E100) was used as solvent to extract the bark using soxhlet extraction method. The extract yields were determined and then subjected to the antibacterial activity assay against S. aureus using disc diffusion method. The phytochemicals content was determined qualitatively reffered to Harborne method. The chemical composition of the extract with the highest antibacterial activity was analyzed by LC-MS and confirmed by FTIR spectroscopy. The study showed that the highest extract yield was obtained in E75 (8.39%), followed by E50 (7.86%), and E100 (6.58%). The extract can inhibited the growth of S. aureus in the range of moderate to strong. The phytochemical analysis and FTIR spectrum confirmed flavonoid, phenolhydroquinone, tannin, saponin, and triterpenoid in the extract. LC-MS analysis showed the presence of (+)-Nootkatone, aurantimide acetate, Vitisin C, Kievitone that suggested have a role in the antibacterial activity against S. aureus
Keyword: antibakteri, konsentrasi pelarut, etanol, meranti, rendemen, sokhlet, antibacterial, ethanol solvent concentration, meranti, soxhlet, yield

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