Judul: Stabilitas larutan kitosan 1,5% sebagai antibakteri pada penyimpanan suhu ruang
Abstrak: Pangan merupakan kebutuhan primer yang sangat vital bagi manusia yang harus terpenuhi terlebih dahulu sebelum kebutuhan yang lainnya. Dewasa ini keberadaan pangan sangat riskan dengan adanya bahaya baik itu yang berasal dari kontaminasi luar maupun yang berasal dari dalam kandungan tersebut. Kerusakan pangan sebagian besar dikarenakan oleh kerja mikroorganisme perusak yang tidak terkontrol baik. Salah satu cara yag dapat dilakukan untuk menjaga keamanan pangan yaitu dengan proses coating atau proses melapisi suatu produk pangan dengan suatu pelapis atau menambahkan zat aditif antibakteri.
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Judul: Aplikasi Kitosan sebagai Edible Coating Antimikroba pada Apel Terolah Minimal.
Abstrak: Penggunaan kitosan sebagai edible coating berpotensi untuk dijadikan sebagai bahan antimikroba, sehingga dapat menghambat pertumbuhan mikroba serta dapat mempertahankan mutu buah dengan menghambat proses respirasi. Penelitian ini bertujuan untuk mengetahui konsentrasi kitosan dan waktu pelapisan yang efektif untuk menghambat pertumbuhan mikroba serta mengetahui pengaruh penggunaan edible coating terhadap mutu buah apel selama penyimpanan. Hasil penelitian menunjukkan bahwa kitosan dengan konsentrasi 2% dengan waktu pelapisan 15 menit dapat mempertahankan mutu buah apel selama penyimpanan. Nilai rata-rata susut bobot, total padatan terlarut, dan kekerasan pada konsentrasi 0% berturutturut yaitu 0,92%; 12,04 brix; dan 14,27 mm/5 detik. Sedangkan pada konsentrasi 2% yaitu 0,71%; 11,06 brix; dan 10,26 mm/5 detik. Nilai lightness dan whiteness menurun sedangkan nilai yellowness meningkat seiring dengan lama waktu penyimpanan. Perlakuan waktu pelapisan tidak memiliki pengaruh yang nyata pada semua parameter mutu. Kitosan dengan konsentrasi 2% mampu menghambat pertumbuhan mikroba dengan nilai rata-rata total mikroba sebesar 3,8 x 104 cfu/g.
Keyword: apel terolah minimal, edible coating, kitosan, antimikroba

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