Judul: Potensi Antibakteri Kitosan sebagai Pengawet Alami pada Tahu
Abstrak: Kitosan merupakan senyawa turunan kitin yang terdapat pada serangga, crustaceae, dan beberapa jenis fungi. Senyawa ini memiliki potensi sebagai antibakteri, termasuk penggunaannya sebagai pengawet n~akanan. Penelitian ini bertujuan menguji potensi antibakteri kitosan sebagai pengawet tahu dan mendapatkan konsentrasi optimal kitosan yang dapat diaplikasikan sebagai pengawet. Perlakuan yang digunakan terdiri atas larutan kitosan (0.05%, 0.1%, 0.2%, dan 0.3%), akuades, larutan natrium benzoat 1%, dan larutan formalin 1%. Pengukuran dan analisis yang dilakukan, yakni pH tahu, angka hitung lempeng total atau Total Plate Count (TPC), dan uji organoleptik (kenampakan, aroma, dan konsistensi). Sifat antibakteri kitosan mampu menghambat laju pertumbuhan bakteri dengan hasil uji statistika berbeda nvala (p<0.05). Larutan kitosan 0.05% merupakan konsentrasi minimum yang optimal dalam menghambat TPC hingga hari ke-6. Pengamatan organoleptik terhadap tahu rnenuniukkan pemberian kitosan memberikan pengaruh yang signifikan (p<0.05)" dalam menjaga kenampakan, aroma, dan konsistensi tahu selama penyimpanan dibandingkan natrium benzoat 1%.
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Judul: Pengaruh Kitosan kulit pupa ulat Sutera Sebagai pengganti Formalin terhadap daya simpan tahu
Abstrak: Kitosan kulit pupa ulat sutera merupakan turunan kitin dari bahan baku kulit pupa ulat sutera yang bisa digunakan sebagai bahan pengawet alami dan aman karena tidak beracun dan memiliki aktivitas antimikroba. Aplikasi kitosan sebagai bahan pengawet pada penelitian ini terhadap kualitas tahu, karena tahu merupakan bahan pangan yang sangat mudah rusak (high perishable food). Tujuan penelitian ini adalah untuk mempelajari pengaruh kitosan terhadap daya simpan tahu. Rancangan percobaan yang digunakan adalah Rancangan Acak Lengkap Faktorial untuk perlakuan perendaman dan lama penyimpanan. Perlakuan kitosan memberikan pengaruh yang nyata (p<0.05) terhadap nilai organoleptik warna dan aroma; nilai pH dan nilai TPC (Total Plate Count) tahu. Perlakuan lama penyimpanan memberikan pengaruh yang nyata (p<0.05) terhadap nilai pH dan nilai organoleptik. Tahu yang diberi perlakuan kitosan 250 ppm memiliki laju kemunduran mutu tahu yang lebih lambat dibandingkan dengan tahu kontrol, formalin 50 ppm, kitosan 500 ppm, dan kitosan 1000 ppm. Kitosan 250 ppm mampu mempertahankan mutu tahu, baik secara organoleptik, proksimat, pH, maupun TPC, Chitosan is a derivative of chitin from silkworm pupae skin that can be used as a natural and safe preservative because it is non-toxic and it has an antimicrobial activity. Application of chitosan as preservative in this research was done on tofu, because tofu is a high perishable food. The purpose of this research was to study the effect of chitosan on storage ability of tofu. The experimental design was a Completely Randomized Factorial Design for immersion treatment and length of the storage treatment. Chitosan treatment resulted a significant effect in organoleptic (color and flavor), pH and TPC (Total Plate Count) scores (p<0.05). Length of the storage treatment also showed a significant effect in pH and organoleptic scores (p<0.05). Tofu treated with 250 ppm chitosan had a lower quality of deterioration rate than control tofu, formalin 50 ppm, chitosan 500 ppm and chitosan 1000 ppm. 250 ppm of chitosan was able to mantain the quality of tofu, in organoleptic, proximate, pH, or TPC aspect.
Keyword: Kitosan, Kulit Pupa, Ulat Sutera, Tahu

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