Judul: Analisis Usahatani dan Tataniaga Jamur Tiram Putih (Studi Kasus: Desa Kertawangi, Kecamatan cisarua, Kabupaten Bandung).
Abstrak: Permintaan konsumsi pangan yang berasal dari bahan baku (komoditas) organik meningkat dengan cepat. Tanaman organik dibudidayakan dengan meminimalkan penggunaan pestisida kimiawi, maka tanaman ini relatif lebih aman. Harga komoditas tanaman organik yang cukup maha1, menyebabkan tidak semua kalangan masyarakat dapat mengkonsumsinya Namun tidak semua komoditas yang aman dari penggunaan pestisida kimiawi memiliki barga beli yang mahal Salah satunya Yaltu jamur tiram (pleurotus ostreoatus). Desa Kertawangi, Kecamatan Cisarua, Bandung merupakan salah satu sentra penanaman jamur tiram.
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Judul: Analisis usahatani jamur tiram putih (Pleurotus ostreatus) (kasus: Desa Kertawangi, Kecamatan Cisarua, Kabupaten bandung, Propinsi Jawa Barat)
Abstrak: Jamur tiram merupakan salah satu jenis produk hortikultura yang dapat dikembangkan dan diarahkan untuk memperbaiki keadaan gizi melalui penganekaragaman jenis bahan makanan. Indonesia sebagai salah satu negara yang berada di daerah tropis memiliki potensi untuk budidaya jamur tiram. Kabupaten Bandung merupakan salah satu daerah sentra produksi jamur tiram putih di Propinsi Jawa Barat. Kecamatan Cisarua merupakan penghasil jamur tiram putih terbesar yaitu 90 persen dari keseluruhan total produksi, sehingga secara tidak langsung sangat berpengaruh dalam menyokong pendapatan masyarakat Kabupaten Bandung. Usahatani jamur tiram putih didukung oleh agroklimat yang cocok serta tersedianya sumber daya manusia. Tujuan penelitian ini adalah untuk menganalisis usahatani jamur tiram putih dan menganalisis faktor produksi yang berpengaruh terhadap usahatani jamur tiram putih. Penelitian ini dilakukan di Desa Kertawangi, Kecamatan Cisarua, Kabupaten Bandung dengan dasar pertimbangan bahwa daerah tersebut merupakan salah satu daerah sentra yang mengembangkan usahatani jamur tiram putih.
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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