Judul: Analisis Karakteristik Fisik Beras Terhadap Harga Beras studi kasus di Bogor
Abstrak: Perbedaan kualitas suatu beras berdampak pada perbedaan harga setiap beras. Salah satu yang menentukan kualitas beras adalah karakteristik fisiknya. Bogor adalah salah satu daerah di Indonesia yang memiliki curah hujan cukup tinggi, sehingga membuat kadar air beras yang berasal dari Bogor tinggi dan menyebabkan kualitas beras rendah. Tujuan penelitian ini adalah untuk mengetahui pengaruh karakteristik fisik beras terhadap harga beras di Bogor. Metode yang digunakan dalam penelitian ini adalah metode analisis deskriptif dan analisis harga hedonik. Hasil penelitian menunjukkan bahwa sebagian besar beras di Bogor termasuk dalam kualitas Premium II berdasarkan masing-masing karakteristik fisiknya. Berdasarkan analisis fungsi harga hedonik, semua variabel bebas yang digunakan berpengaruh signifikan terhadap harga. Namun hanya variabel butir menir, butir rusak, dan rasio panjang/lebar yang berpengaruh secara nyata terhadap harga beras di Bogor.
Keyword: beras, fungsi harga hedonik, harga, karakteristik fisik, kualitas

Judul: Analisis Tingkat Kepentingan dan Kepuasan Konsumen Terhadap Atribut Mutu Beras Berlabel Serta Perilaku Konsumen Dalam Pembelian Beras Berlabel
Abstrak: Beras berlabel adalah beras non curah yang dalam kemasannya mencantumkan informasi mengenai produk pada konsumen. Jenis beras yang paling mudah ditemui di pasaran adalah Pandan Wangi, Setra Ramos, Rojolele, dan Cianjur. Penelitian ini bertujuan mengetahui tingkat kepentingan dan kepuasan konsumen terhadap atribut mutu beras berlabel yang dianggap penting, serta mengetahui perilaku konsumen dalam pembelian beras berlabel di wilayah Bogor. Atribut mutu yang dianalisis adalah rasa, kepulenan, aroma, warna, kebersihan, kontaminasi serangga, bahan kemasan, dekorasi kemasan, informasi, harga, merek, ketersediaan, dan sertifikat jaminan keaslian varietas. Sementara itu, perilaku yang dianalisis adalah tempat pembelian, ukuran kemasan, jenis beras, harga beras, dan merek. Penelitian ini dilaksanakan di wilayah kota Bogor. Sampel diambil dari pengunjung pasar swalayan di wilayah kota Bogor sebanyak 100 orang. Penelitian dilaksanakan dari bulan November sampai dengan Desember 2006, dengan metode non probability sampling yaitu quota sampling. Pengumpulan data dilakukan dengan cara pengisian kuisioner oleh lima orang enumerator, termasuk peneliti.
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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