Judul: Produksi Pemasaran dan Tingkat Pendapatan Petani di Wilayah  Kerja Usahatani Model Daerah Aliran Sungai Citanduy KEcamatan Rancah dan Rajadesa Kabupaten Ciamis, Jawa Barat (Suatu Studi Kasus)
Abstrak: Pengembangan model farm dan areal dampaknya menyebabkan adanya peningkatan produksi, khususnya produksi tanaman pangan semusim seperti padi gogo, jagung, kacang-kacangan, 1 abu besar, mentimun dan ubi kayu. Peningkatan produksi ini harus disertai oleh lancarnya pemasaran karena lancarnya pemasaran suatu produk akan menjaga kekontinuitasan produk tersebut. Sedangkan lancarnya pemasaran sangat ditentukan oleh kegiatan pasca panen sebelumnya dan kebijasanaan harga produk. Harga produk yang di terima petani berkaitan erat dengan pendapatan petani.
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Judul: Analisis Pendapatan Usaha Tani Petani Peserta Model Farm Dan NON Model Farm Proyek Citanduy II : Studi Kasus Di Desa Panyutran Kecamatan Pada Herang Kabupaten Ciamis
Abstrak: Tanah, air dan hutan merupakan unsur-unsur penting sektor pertanian yang perlu dipertahankan kelestariannya. Daerah Aliran sungai merupakan daerah potensial terjadi- nya penurunan kualitas lahan serta erosi yang dapat berakibat banjir dan terbentuknya sedimentasi. Model Farm adalah salah satu bentuk penerapan teknologi lahan kering di daerah Hulu DAS Citanduy, yang bertujuan untuk menanggulangi masalah erosi dan meningkatkan pendapatan petani di daerah hulu DAS Citanduy. Tujuan penelitian ini adalah untuk melihat secara langsung kegiatan usahatani di lahan model farm. Secara khusus penelitian praktek lapang ini juga bertujuan untuk melihat pengaruh model farm terhadap penyerapan tenaga kerja, serta melihat tingkat pendapatan petani Model farm dan non model farm. Sebagai pelengkap akan di analisis pula pengaruh tingkat perhatian petani kepada Model farm terhadap keberhasilan Model Farm.
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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