Judul: Aktivitas Antioksidan Gel Ekstrak Buah Bisbul (Diospyros discolor Willd.) dengan Metode DPPH.
Abstrak: Buah bisbul (Diospyros discolor Willd.) adalah buah yang awalnya tumbuh liar di hutan-hutan Filipina, dan kini telah menyebar di Indonesia. Buah bisbul berpotensi mengandung senyawa antioksidan. Tujuan penelitian ini adalah menguji aktivitas ekstrak buah bisbul dan gel ekstrak buah bisbul sebagai antioksidan dengan menggunakan metode DPPH. Buah bisbul diekstraksi dengan metode maserasi dan menggunakan etanol 96% sebagai pelarutnya. Penapisan fitokimia menunjukkan bahwa ekstrak buah bisbul mengandung flavonoid, tanin, dan saponin. Ekstrak buah bisbul memiliki aktivitas antioksidan sangat kuat dengan nilai IC50 46.00 ppm, namun gel ekstrak buah bisbul memiliki aktivitas antioksidan sangat lemah dengan nilai IC50 33286.00 ppm.
Keyword: aktivitas antioksidan, buah bisbul, ekstraksi, penapisan fitokimia

Judul: Uji Aktivitas Antioksidan Gel Ekstrak Batang Buah Naga Merah (Hylocereus polyrhizus) dengan Metode DPPH.
Abstrak: Batang buah naga merah atau Hylocereus polyrhizus mempunyai kandungan metabolit sekunder yang berperan aktif sebagai antioksidan. Tujuan dari penelitian ini adalah untuk menguji aktivitas antioksidan ekstrak dan gel ekstrak batang buah naga merah. Hasil analisis fitokimia menunjukkan ekstrak batang buah naga merah mengandung alkaloid, flavonoid dan steroid. Aktivitas antioksidan ditentukan dengan metode DPPH. Ekstrak batang buah naga merah memiliki nilai IC50 sebesar 1020.95 ppm dan gel ekstrak batang buah naga merah memiliki nilai IC50 sebesar 77601187.54 ppm. Semakin rendah IC50, maka aktivitas antioksidan semakin tinggi. Berdasarkan uji yang dilakukan, ekstrak dan ekstrak gel memiliki aktivitas antioksidan sangat lemah dengan nilai IC50 lebih dari 200 ppm.
Keyword: antioksidan, batang buah naga merah, DPPH, fitokimia, gel

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