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: Kadar Total Fenolik, Flavonoid, dan Aktivitas Antioksidan Madu Monoflora Lebah Apis mellifera Akibat Perlakuan Pemanasan
Abstrak: Perlakuan pemanasan terhadap madu diketahui dapat memengaruhi kandungan senyawa yang terdapat dalam madu. Pemanasan dilakukan pada tiga suhu berbeda yaitu suhu 32 ℃ (suhu ruang), 65 ℃, dan 121 ℃ dengan pengujian kadar total fenolik, flavonoid, DPPH dan FRAP. Penelitian bertujuan menentukan suhu pemanasan terbaik yang menghasilkan kadar fenolik, flavonoid, dan aktivitas antioksidan madu monoflora tertinggi, dan menganalisis korelasi antara kadar fenolik dan flavonoid dengan aktivitas antioksidan yang diperoleh. Korelasi dianalisis dengan uji Pearson. Madu akasia karpa memiliki nilai kadar total fenolik tertinggi sebesar 1967,5 mg GAE/100 gram, sedangkan untuk kadar total flavonoid dan aktivitas antioksidan meliputi DPPH dan FRAP tertinggi yaitu pada madu mangga, secara berturut-turut sebesar 482,06 mg QE/100 gram, 9,91 g/L dan 12,94 μmol TEAC/g. Hasil penelitian ini menunjukkan pemberian perlakuan pemanasan 121 ℃ meningkatkan kadar fenolik, flavonoid, maupun aktivitas antioksidan pada madu monoflora. Namun demikian, pemanasan 65 ℃ dan 121 ℃ tidak memberikan korelasi terhadap kadar fenolik, flavonoid, dan aktivitas antioksidan., Heating treatment of honey is known to affect the content of compounds contained in honey. Heating was carried out at three different temperatures, namely 32 ℃ (room temperature), 65 ℃, and 121 ℃ with testing of total phenolic, flavonoid, DPPH and FRAP levels. The study aims to determine the best heating temperature that produces the highest levels of phenolics, flavonoids and antioxidant activity of monoflora honey, and to analyse the correlation between phenolic and flavonoid levels and antioxidant activity obtained. Correlations were analysed using the Pearson test. Acacia karpa honey had the highest value of total phenolic content of 1967,5 mg GAE/100 grams, while for total flavonoid content and antioxidant activity including DPPH and FRAP the highest was in mango honey, respectively 482,06 mg QE/100 grams, 9,91 g/L and 12,94 μmol TEAC/g. The results of this study showed that 121 ℃ heating treatment increased the phenolic content, flavonoids, and antioxidant activity in monoflora honey. However, 65 ℃ and 121 ℃ heating did not correlate with phenolic, flavonoid, and antioxidant activities.
Keyword: antioxidant, flavonoid, heat treatment, monoflora 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