Judul: Karakterisasi Fisikokimia dan Aktivitas Antioksidan Madu dari Beberapa Daerah di Indonesia
Abstrak: Konsumsi madu telah dilakukan sejak ratusan tahun yang lalu dan dipercaya memiliki nilai nutrisi yang tinggi dan nilai fungsional. Indonesia berpotensi sebagai penghasil madu, namun belum diketahui kualitas madu-madu tersebut apabila dibandingkan dengan Standar Nasional Indonesia (SNI). Penelitian ini bertujuan untuk mengkarakterisasi dan mengukur aktivitas antioksidan sampel madu dari beberapa daerah di Indonesia. Karakteristik madu dianalisis berdasarkan Standar Nasional Indonesia (SNI) 2013, yang meliputi: kadar air, kadar abu, gula pereduksi, dan hidroksimetilfurfural (HMF). Metode yang digunakan untuk mengukur aktivitas antioksidan sampel madu yaitu menggunakan metode 2,2-diphenil 1-pichyl hydazyl (DPPH). Terdapat lima sampel madu yang lolos uji karakterisasi fisikokimia, yaitu sampel madu S1, TK1, RMBTN, KLKNG, dan MRV. Nilai IC50 dari kelima sampel madu tersebut adalah 18.18 ppm, 20.47 ppm, 15.08 ppm, 14.78 ppm, dan 15.94 ppm. Hasil pengukuran aktivitas antioksidan pada kelima madu terpilih membuktikan bahwa madu memiliki potensi kandungan antioksidan.
Keyword: antioksidan, HMF, kadar abu, kadar air, madu

Judul: Kadar Total Fenolik, Flavonoid, dan Aktivitas Antioksidan Madu Lebah Tanpa Sengat (Trigona sp.) Akibat Pemanasan
Abstrak: Konsumsi madu dapat mencegah permasalahan kesehatan di Indonesia. Beragam madu ditemukan di Indonesia, salah satunya madu kelulut. Umur penyimpanan madu dapat diperpanjang dengan pemanasan. Pemanasan berpengaruh terhadap kelembapan, viskositas, kadar air, kadar fenolik, kadar flavonoid, dan antioksidan madu. Pemanasan madu meliputi suhu 65℃ dan 121℃ serta stanpa pemanasan sebagai kontrol dengan pengujian kadar total fenolik, flavonoid, DPPH, dan FRAP. Tujuan dari penelitian ini adalah menentukan suhu yang ideal pada pemanasan madu sehingga didapat kadar total fenolik, flavonoid, dan aktivitas antioksidan tertinggi. Sampel madu kelulut Pandeglang 2 memiliki kadar total fenolik dan total flavonoid tertinggi pada pemanasan 121℃ sebesar 18,50 mg GAE/g madu dan 10,80 mg QE/g madu, sedangkan nilai IC50 DPPH dan aktivitas antioksidan FRAP tertinggi diperoleh dari sampel Pandeglang 1 yakni sebesar 10,01 mg/mL dan 12,09 µmol TEAC/g madu. Simpulan penelitian ini adalah kadar total fenolik, flavonoid, dan aktivitas antioksidan optimal pada suhu pemanasan 121℃.
Keyword: antioxidant, flavonoid, heat treatment, kelulut honey, phenolic

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