Judul: Perilaku Konsumsi Suplemen pada Pria Dewasa di Kota Jakarta Selatan
Abstrak: Penelitian ini bertujuan untuk mengetahui perilaku konsumsi suplemen dikalangan pria dewasa di Jakarta Selatan; meliputi jenis dan bentuk suplemen frekuensi dan tingkat konsumsi suplemen, atribut dan alasan mengkonsumsi suplemen. Contoh adalah pria dewasa (20-60 tahun) yang mengkonsumsi suplemen / minimal (satu) kali sebulan terakhir. Pengumpulan data dilakukan pada bulan April sampai Juni 2001 dengan metode telephone interview di Kota Jakarta Selatan. Berdasarkan data buku petunjuk telepon Jakarta Selatan, jumlah nomor telepon di Jakarta Selatan sekitar 200.000 nomor. Dari jumlah tersebut diambil 1.000 nomor telepon yang masing-masing 40 rumah tangga pelanggan telepon dari huruf A-Z kecuali huruf X. Dari 1.000 rumah tangga yang ditelepon, 903 dapat dihubllngi, dan diantaranya (27,13%) rumah tangga memiliki pria dewasa yang pernah mengkonsumsi suplemen selama sebulan terakhir. Jumlah yang dapat dijadikan contoh adalah 209 orang. Disain penelitian adalah Cross Sectional Study dengan metode survei.
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Judul: Perilaku Konsumsi Suplemen Pangan (Food Supplement) Pada Wanita Dewasa Di Kota Jakarta Pusat
Abstrak: Tujuan penelitian ini adalah untuk mengetahui perilaku konsumsi suplemen (food supplement) pada wanita. Penelitian ini dilakukan di Jakarta Pusat pada Bulan Maret sampai Mei 2002. Contoh berjumlah 244 wanita usia 20-60 tahun yang mengkonsumsi suplemen minimal satu kali dalam satu bulan terakhir dan bersedia diawawancarai melalaui telepon, setelah sebelumnya dilakukan pengacakan secara sistematik terhadap 89188 sambungan telepon rumahtangga di Jakarta Pusat dan dipilih 1200 nomor telepon. Data yang dikumpulkan melalui wawancara via telepon antara lain meliputi karakteristik contoh, jenis dan bentuk suplemen, frekuensi, jumlah konsumsi alasan dm manfaat konsumsi suplemen, tempat memliki dan sumber informasi, karakteristik produk serta hasil analis antara karakteristik contoh dengan frekuensi dan jumlah konsumsi
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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