Judul: Aktivitas Antioksidan Ekstrak Etanol dan Profil Metabolit Sekunder Tanaman Kembang Telang (Clitoria ternatea)
Abstrak: Tanaman kembang telang (Clitoria ternatea) banyak digunakan dalam pengobatan tradisional dan berpotensi sebagai antioksidan. Tujuan penelitian adalah membandingkan kemampuan antioksidan ekstrak etanol kembang telang dan profil metabolit fraksi n-heksana pada setiap bagian tanaman. Kembang telang ditanam selama 12 minggu sebanyak 30 tanaman di kebun percobaan IPB Cikabayan. Pengukuran tanaman meliputi tinggi tanaman, jumlah daun, diameter batang serta produksi tanaman yang selalu meningkat selama percobaan Kandungan fenolik tertinggi dari setiap bagian tanaman (akar, bunga, daun dan batang) adalah akar dengan kandungan fenolik sebesar 83.45 mg GAE/g. Sedangkan kandungan flavonoid tertinggi adalah daun dengan nilai total flavonoid sebesar 5.96 mg EK/g. Kandungan antosianin hanya dimiliki oleh bunga dan daun. Aktivitas antioksidan tertinggi (nilai IC50 yang rendah) dari setiap bagian tanaman adalah akar dengan nilai IC50 sebesar 106.973 μg/mL. Hasil GC-MS bagian akar menunjukkan 13 senyawa yang teridentifikasi, bagian bunga sebanyak 12 senyawa, bagian daun sebanyak 11 senyawa dan bagian batang sebanyak 9 senyawa yang teridentifikasi.
Keyword: antioksidan, ekstrak etanol, kembang telang, GC-MS, metabolit sekunder

Judul: Potensi Ekstrak Bunga Telang (Clitoria ternatea) sebagai Antioksidan dan Inhibitor Tirosinase
Abstrak: Clitoria ternatea yang dikenal dengan nama bunga telang adalah tanaman yang banyak digunakan dalam bidang kesehatan seperti antidiabetes, antiinflamasi, antimikroba, antikanker, analgesik, antipiretik dan mengandung kandungan metabolit sekunder yang berperan aktif sebagai antioksidan. Tujuan penelitian ini adalah untuk menguji aktivitas antioksidan ekstrak bunga telang dan inhibitor tirosinase serta mengidentifikasi kandungan fitokimianya. Aktivitas antioksidan ditentukan dengan metode DPPH (2,2-difenil-1-pikrihidrasil). Hasil penelitian ini menunjukkan bahwa, ekstrak bunga telang memiliki aktivitas antioksidan yang sangat lemah dengan nilai IC50 (Inhibition Concentration 50%) lebih dari 200 ppm. Hasil dari aktivitas inhibitor tirosinase menunjukkan bahwa ekstrak bunga telang tidak aktif dalam menghambat enzim tirosinase. Berdasarkan pengujian penapisan fitokimia, komponen kimia yang terkandung dalam ekstrak bunga telang adalah golongan flavonoid, tanin, saponin dan steroid.
Keyword: antioksidan, Clitoria ternatea, DPPH, fitokimia, tirosinase

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