Judul: Antioxidant Capacity of Kayu Bajakah Tree Bark and Cakar Ayam Leaf Extracts at Various Ethanol Concentrations
Abstrak: Radikal bebas adalah molekul yang sangat reaktif dan dapat diatasi dengan antioksidan. Apabila jumlahnya melebihi kemampuan antioksidan, dapat menyebabkan stres oksidatif yang berujung pada penyakit seperti kanker. Tanaman yang dapat berpotensi sebagai sumber antioksidan alami, yaitu kayu bajakah dan daun cakar ayam. Penelitian ini bertujuan menentukan konsentrasi pelarut etanol terbaik dan pengaruh kombinasi dari ekstrak kayu bajakah dan daun cakar ayam berdasarkan kapasitas antioksidan. Tiga variasi sampel (bajakah 100%, daun cakar ayam 100%, dan kombinasi 50:50) diekstraksi menggunakan 5 konsentrasi etanol (10%, 30%, 50%, 70%, dan 96%). Skrining fitokimia dilakukan secara kualitatif. Penetapan kapasitas antioksidan menggunakan metode DPPH dan FRAP dengan perhitungan nilai trolox equivalent antioxidant capacity (TEAC). Hasil penelitian ini menunjukkan ekstrak kayu bajakah dan daun cakar ayam positif mengandung flavonoid, alkaloid, tanin, dan fenol. Kapasitas antioksidan metode DPPH menunjukkan nilai tertinggi pada sampel kombinasi dengan etanol 70% (15,07 µmol TE/g), sedangkan metode FRAP menunjukkan nilai tertinggi pada sampel kombinasi dengan etanol 50% (33,17 µmol TE/g).
Keyword: DPPH, fitokimia, FRAP, radikal bebas

Judul: Antioxidant Activity of Merbau Wood Extracted  from Various Concentrations of Ethanol
Abstrak: Kayu merbau merupakan salah satu bahan yang mengandung antioksidan alami. Antioksidan merupakan senyawa yang dapat menghambat reaksi radikal bebas. Penelitian ini bertujuan menentukan rendemen hasil ekstraksi kayu merbau (Intsia bijuga) dari berbagai konsentrasi etanol, menguji aktivitas antioksidan, dan mengidentifikasi fitokimia ekstrak prospektif. Serbuk kayu merbau bagian teras diekstraksi menggunakan metode maserasi dengan pelarut etanol pada konsentrasi etanol 100% (E100), 75% (E75), 50% (E50), 25% (E25), dan air (E0). Ekstrak kemudian diuji aktivitas antioksidannya secara in vitro terhadap radikal bebas 2,2-difenil-1-pikrilhidrazil (DPPH). Ekstrak prospektif ditentukan berdasarkan aktivitas antioksidan serta rendemennya, kemudian dianalisis fitokimianya dengan Liquid chromatography–mass spectrometry (LC–MS). Hasil penelitian menunjukkan rendemen ekstraksi kayu merbau dipengaruhi konsentrasi etanol. Rendemen tertinggi dihasilkan dari ekstraksi dengan E50 (17,79%) dan yang terendah adalah E0 (11,11%). Aktivitas antioksidan kelima ekstrak tergolong kuat (IC50 5,68–9,37 ppm) dibandingkan dengan troloks (IC50 9,78 ppm). Aktivitas antioksidan tertinggi adalah ekstrak terlarut E50 dengan nilai IC50 5,68 µg/mL. Hasil analisis LC-MS menunjukkan bahwa ekstrak terlarut E50 mengandung senyawa utama seperti robidanol (46,3%), robinetin (31,5%), dan katekin (7,2%).
Keyword: antioksidan, kayu merbau, DPPH, ekstrak etanol

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