Judul: Beberapa Faktor Ekonomi yang Mempengaruhi Fertilitas di Kotamadya Manado
Abstrak: Tujuan penelitian adalah untuk mengetahui sejauh mana pendapatan keluarga, biaya pemeliharaan anak dan kesempatan kerja wanita khususnya ibu rumah tangga mempengaruhi fertilitas. Penelitian in dilaksanakan di kotamadya Manado dengan objek penelitian adalah keluarga yang tergantung pasangan Usia Subur. Hasil penelitian menunjukan bahwa pendapatan keluarga tidak menunjukkan pengaruh yang nyata terhadap tingkat fertilitas namun terhadap kecenderungan bahwa semakin tinggi pendapatan maka fertilitas akan semakin meningkat.
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Judul: Faktor Faktor Sosial Ekonomi Yang Mempengaruhi Fertilitas (Kasus di Desa Ciapus dan Padasuka Kecamatan Ciomas, Kabupaten Bogor
Abstrak: Tujuan penelitian ini adalah untuk mengetahui 1) hu- bungan antara faktor sosial ekonomi dengan fertilitas dan 2) hubungan kausal antara faktor-faktor sosial ekonomi de- ngan fertilitas dengan memperhatikan status kerja. Untuk mencapai tujuan tersebut digunakan teori aloka- si waktu dari Becker serta teori fertilitas dari Ronald Freedman dan Davis dan Blake. Fertilitas dianalisis dengan menggunakan konsep pengambilan keputusan yang tercermin da- lam bentuk jumlah anak lahir hidup (JALH). Ponelitian ini dilakukan di dua desa yaitu Desa Cia- pus yang bercirikan desa pertanian dan Desa Padasuka yang bercirikan desa non pertanian dengan menggunakan metode studi kasus. Data yang dikumpulkan adalah data kuantitatif dan kualitatif, Unit yang dianalisis adalah individu se- banyak 120 orang yang terdiri dari 60 orang ibu yang ti- dak bekerja dan 60 orang ibu yang bekerja di pertanian dan non pertanian. Usia Ibu antara 15 sampai 49 tahun dan minimal nenpunyai satu orang anak. ...
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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