Judul: Studi pemasaran Ikan Bandeng (Chanos Cchanos Forsk) dari Desa Tambaksari, Kabupaten Karawang Ke DKI Jakarta
Abstrak: Ikan Bandeng (Chanos chanos Forsk) merupakan produksi utama dari tambak tumpangsari di Desa Tambaksari, Kabupaten Karawang. Sebagai ikan yang tergolong ekonomis penting, ikan bandeng tersebut disalurkan oleh lembaga. pemasaran yang ada ke daerah konsumen di DKI Jakarta. Penelitian ini bertujuan untuk: (1) mengetahui gambaran umum pemasaran ikan bandeng dari Desa Tambaksari, Kabupaten Karawang ke DKI Jakarta yang meliputi saluran pemasaran, fungsi-fungsi pemasaran yang dilakukan oleh lembaga pemasaran yang terlibat dan permasalahan yang ada dalam kegiatan pemasaran tersebut, (2) mempelajari penyebaran margin pemasaran diantara lembaga pemasaran dan mengetahui besarnya farmers' share, (3) mengetahui hubungan antara farmers' share dengan total biaya pemasaran dan total keuntungan pemasaran.
Keyword: ikan bandeng

Judul: Analisis Efisiensi Pemasaran Ikan Bandeng di Kecamatan Tirtajaya Kabupaten Karawang
Abstrak: Kabupaten Karawang merupakan sentra produksi ikan bandeng di Jawa Barat. Produksi ikan bandeng terus meningkat, namun harga ikan bandeng berfluktuasi. Fluktuasi harga menyebabkan ketidakpastian pendapatan baik bagi petani sebagai produsen maupun pedagang sebagai lembaga pemasaran. Fluktuasi harga sangat erat kaitannya dengan sistem pemasaran. Tujuan penelitian ini adalah mengetahui sistem pemasaran dan efisiensi pemasaran ikan bandeng di Kecamatan Tirtajaya Kabupaten Karawang. Hasil penelitian menunjukkan bahwa terdapat enam saluran pemasaran ikan bandeng di Kecamatan Tirtajaya, Kabupaten Karawang. Lembaga pemasaran yang terlibat didalamnya antara lain petani, pedagang pengumpul desa, pedagang besar, pedagang pengecer dan pengolah. Dilihat dari nilai marjin pemasaran dan farmer’s share, seluruh saluran pemasaran ikan bandeng sudah efisien. Dari seluruh saluran pemasaran, saluran pemasaran 1 merupakan saluran yang relatif lebih efisien dengan nilai marjin terendah sebesar 9.71 persen dan farmer’s share tertinggi sebesar 90.29 persen. Nilai rasio keuntungan atas biaya pada seluruh lembaga pemasaran telah menyebar secara merata.
Keyword: milkfish, marketing efficiency, marketing margin

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