Judul: Analisis Strategi Pemasaran Ekspor Teh Hitam Pada Kantor Pemasaran Bersama (KPB) PT Perkebunan Nusantara, Jakarta
Abstrak: Salah satu sub sektor pertanian yang memiliki peranan penting dalam menghasilkan komoditas ekspor dari sektor non migas adalall perkebunan. The merupakan hasil perkebunan yang menjadi bagian dari komoditas pertanian utama ekspor non migas Indonesia yang berfungsi sebagai penghasil devisa negara dan sebagai penyedia lapangan pekerjaan. Pada tahun 2000 Indonesia merupakan Negara produsen teh keenam dunia dan peringkat kelima negara eksportir teh dunia. Di Indonesia teh dihasilkan oleh tiga jenis badan usaba, yaitu perkebunan besar negara, perkebunan besar swasta dan perkebunan rakyat.
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Judul: Analisis daya saing teh hitam dan pengembangan wisata agro di PT.Perkebunan Nusantara VIII, Jawa Barat
Abstrak: Teh merupakan penghasil devisa yang cukup besar. Selain menghasilkan devisa pengusahaan teh juga berperan terhadap peningkatan taraf hidup petani, penyedia lapangan kerja, pemenuhan kebutuhan di dalam negeri, dan pemeliharaan sumberdaya alam. Pada saat ini perdagangan teh hitam di pasar intemasional mengalami kelebihan penawaran yang disebabkan peningkatan produksi teh hitam yang tidak diimbangi dengan laju peningkatan konsumsi. Kondisi kelebihan penawaran ini mengakibatkan jatuhnya harga teh hitam di pasaran dunia, sehingga volume, nilai, dan pangsa ekspor teh hitam Indonesia menurun di pasar intemasional. Mengingat tidak menentunya situasi pasar teh hitam dunia, upaya yang tepat dilakukan oleh produsen Indonesia adalah dengan menggarap pasar dalam negeri, karena konsumsi teh per kapita di Indonesia masih rendah, apabila dibandingkan dengan negara-negara produsen teh hitam lainnya, sehingga perlu dilakukan usaha­ uasaha promosi. Salah satu bentuk promosi yang dilakukan oleh perkebunan­ perkebunan teh adalah melakukan penganekaragaman usaha dengan mengadakan wisata agro. Selain sebagai alat promosi, wisata agro juga diharapkan dapat meningkatkan kesempatan kerja dan pendapatan masyarakat sekitamya.
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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