Judul: Kualitas mikrobiologis karkas ayam broiler selama pemasaran pada pasar tradisional di Bogor
Abstrak: Chicken meat is an important protein source which has relatively low in price. The demand of chicken carcass increases year by year, but it is not followed by the development of carcass handling procedurs in traditional market, especially in Indonesia This fact resulted that chicken carcass easily conlaminated by microorganism, so the quality decreased In traditional market, chicken carcass sold in open air and room tempemhm without any package. The objective of this research was to study microbial quality of broiler carcass during marketing process on traditional market in Bogor. This research studied about total microorganism, total coliform and Salmonella, in 6 hour marketing process in traditional market.
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Judul: The Quality and Total Microbe of Chicken Carcass at One of Traditional and Modern Market at Kabupaten Bogor
Abstrak: Produk peternakan seperti daging ayam merupakan sumber protein hewani dengan mutu protein yang tinggi dan kandungan asam amino esensial yang lengkap. Sumber protein hewani tersebut dapat menjadi rusak seperti menurunnya mutu serta tingginya kandungan mikroba jika tidak mendapatkan penanganan yang benar. Penanganan tersebut dimulai sejak pemotongan, transportasi serta pada saat penjualan. Alur proses penanganan tersebut dilakukan pada pedagang yang melakukan pemotongan ayam di rumah pemotongan ayam (RPA). Berbeda dengan pemotongan RPA, pedagang yang melakukan pemotongan langsung di tempat penjualan hanya memperhatikan saat pemotongan dan penjualan karkas ayam. Penelitian ini bertujuan untuk mempelajari mutu dan total mikroba karkas ayam pada salah satu pasar tradisional dan modern yang berupa pasar swalayan di Kabupaten Bogor. Penelitian ini menggunakan sampel karkas ayam yang berasal dari pedagang pasar tradisional dengan pemotongan di tempat penjualan, pedagang pasar tradisional dengan pemotongan di RPA dan swalayan. Peubah yang diamati adalah mutu dan total mikroba pada karkas ayam dari ketiga jenis sampel yang menjadi target penelitian. Data yang diperolah disajikan secara deskriptif. Hasil pengklasifikasian mutu kasrkas berdasarkan kriteria SNI 01-3924-2009 menunjukkan bahwa karkas yang diambil dari pedagang pasar tradisional yang melakukan pemotongan di tempat penjualan memiliki tingkatan mutu terbaik yaitu mutu I sebanyak 33,3%, mutu II sebanyak 66,7%, dan mutu III sebanyak 0% untuk sampel. Cemaran mikroba berdasarkan SNI 01-2897-2008 menunjukkan bahwa total mikroba terendah juga didapat dari sampel yang diambil dari pedagang pasar tradisional yang melakukan pemotongan di tempat penjualan yaitu sebanyak 6,6 x 104 cfu/g pada bagian dada dan 9,5 x 104 cfu/g pada bagian paha. Namun demikian, pemotongan ayam di tempat penjualan dapat menimbulkan resiko penyebaran penyakit zoonosis serta pencemaran limbah di pasar. Sebagai kesimpulan, peningkatan mutu dan penghambatan pertumbuhan mikroba pada karkas harus dilakukan melalui manajemen RPA yang baik, sistem rantai dingin dan manajemen karkas yang baik di tempat penjualan.
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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