Judul: Senyawa yang Teridentifikasi dalam Ekstrak Metanol Temu Putih (Curcuma zedoaria).
Abstrak: Temu putih (Curcuma zedoaria) merupakan tanaman Zingiberacae yang banyak digunakan sebagai obat tradisional. Penelitian ini bertujuan mengisolasi metabolit sekunder pada fraksi metanol rimpang temu putih dan diidentifikasi senyawanya dengan kromatografi gas dan spektrometer massa (GC-MS). Ekstrak metanol temu putih yang diperoleh adalah 20%. Pemurnian menggunakan kromatografi radial dan kromatografi lapis tipis preparatif menghasilkan 2 fraksi, yaitu 3A1 dan 3A2 yang kemudian dianalisis dengan menggunakan GC-MS. Senyawa yang teridentifikasi dalam fraksi 3A1 sebanyak 47, termasuk 2 senyawa yang diduga sebagai lippifoli-1(6)-en-4β-ol-5-on dan benzotiazola-2-tiol. Senyawa yang teridentifikasi dalam fraksi 3A2 sebanyak 58, termasuk diantaranya α-siperon, madolin A, 1,6-dimetil-9-(1-metiletilidena)-5,12-dioksatrisiklododekan- 8-on, dan benzo[1,2-b:4,3-b']dipiran-3,6-dion-2,2-dimetil.
Keyword: α-siperon, GC-MS, lippifoli-1(6)-en-4β-ol-5-on, madolin A, temu putih

Judul: Penapisan Fitokimia, Ekstraksi, Fraksionasi, dan Studi Pustaka Potensi Bioaktivitas Temu Putih (Curcuma zedoaria).
Abstrak: Temu putih (Curcuma zedoaria) merupakan tanaman asli India, termasuk famili Zingiberaceae yang banyak digunakan dalam industri parfum, pewarna, pangan, dan sebagai obat atau campuran obat. Penelitian sebelumnya melaporkan rimpang ini mengandung alkaloid, fenolik, flavonoid, saponin, glikosida, steroid, dan terpenoid. Senyawa aktifnya diduga dapat digunakan sebagai antimikrob, antifungi, antikanker, antialergi, antioksidan, dan analgesik. Penelitian ini bertujuan menapis fitokimia, memfraksionasi fraksi etil asetat, dan menelusur pustaka mengenai potensi bioaktivitasnya. Rendemen ekstrak metanol mencapai 10% dan setelah dipartisi didapatkan rendemen fraksi etil asetat 55%. Fraksi etil asetat selanjutnya difraksionasi menggunakan kromatografi cair vakum dan ditapis fitokimianya. Senyawa metabolit sekunder yang terkandung berupa flavonoid, triterpenoid, dan alkaloid. Menurut pustaka, senyawa dalam ekstrak ini memiliki aktivitas antibakteri.
Keyword: alkaloid, antibakteri, flavonoid, temu putih, triterpenoid

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