Judul: Studi Pustaka Senyawa Terpenoid dari Daun Pinus Cook (Araucaria columnaris) dan Bioaktivitasnya sebagai Antibakteri
Abstrak: Infeksi bakteri merupakan penyakit serius yang dapat diobati menggunakan obat antibakteri. Tanaman pinus cook (Araucaria columnaris) telah diketahui memiliki aktivitas antibakteri yang sering dikaitkan dengan komponen metabolit sekunder dari golongan nonfenolik seperti terpenoid. Oleh karena itu, penelitian ini bertujuan mengeksplorasi senyawa terpenoid yang teridentifikasi dari daun pinus cook, mengumpulkan informasi mengenai aktivitas antibakteri, dan mengkaji hubungan struktur terpenoid dengan aktivitasnya sebagai antibakteri. Golongan seskuiterpenoid dan diterpenoid mendominasi minyak atsiri dari daunnya. Terdapat 36 senyawa terpenoid yang teridentifikasi, diantaranya 1 monoterpenoid, 23 seskuiterpenoid, 9 diterpenoid dan 3 triterpenoid. Sebagian besar terpenoid yang teridentifikasi memiliki aktivitas antibakteri yang kuat baik terhadap bakteri Gram positif maupun Gram negatif dan umumnya bersifat bakteriostatik. Selain itu, terpenoid dengan ikatan rangkap memiliki aktivitas antibakteri yang lebih kuat dibandingkan terpenoid tanpa ikatan rangkap.
Keyword: antibacterial, Araucaria columnaris, cook pine, leaves, terpenoids

Judul: Literature Study of Biflavonoids from Cook Pine (Araucaria columnaris) Leaves and Its Bioactivity as Antidiabetic Agent
Abstrak: Diabetes melitus merupakan penyakit yang sangat berbahaya yang dapat diobati menggunakan obat herbal yang mengandung senyawa biflavonoid. Anggota famili Araucariaceae yang mengandung senyawa ini adalah Araucaria columnaris. Penelitian ini bertujuan menelusur senyawa yang terkandung pada spesies ini dan potensinya sebagai antidiabetes. Sumber pustaka ialah publikasi pada tahun 2000 hingga 2021. Kajian ini menunjukkan bahwa A. columnaris mengandung senyawa biflavonoid, hidrokarbon, terpenoid, dan metabolit sekunder lainnya. Amentoflavon (suatu biflavonoid) yang ditemukan pada daun tumbuhan ini berpotensi sebagai antidiabetes. Amentoflavon bekerja dengan cara menghambat aktivitas enzim α-glukosidase. Aktivitas antidiabetesnya akan meningkat seiring dengan bertambahnya gugus metoksi pada kerangka biflavonoid dengan tetap mempertahankan gugus hidroksil pada posisi posisi C4‴., Diabetes mellitus is a perilous disease that can be treated using herbal remedies containing biflavonoid compounds. A member of the family Araucariaceae containing this compound is Araucaria columnaris. This study aims to explore the compounds contained in this species and its potential as antidiabetic. The literature source is publications from 2000 to 2021. This study shows that A. columnaris contains biflavonoids, hydrocarbons, and terpenoids. Amentoflavones (a biflavonoid) found in the leaves of this plant have the potential to be antidiabetic. Amentoflavones work by inhibiting the activity of α-glucosidase enzymes. Its antidiabetic activity will increase as the methoxy group increases in the biflavonoid skeleton while maintaining the hydroxyl group at the C4‴ position.
Keyword: A. columnaris, amentoflavon, antidiabetes, Biflavonoid, Pinus cook, amentoflavone, antidiabetic, cook pine

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