Judul: Kajian Paparan Bisfenol-A (BPA) Dari Botol Susu Polikarbonat Pada Bayi. Studi Kasus : Wilayah DKI Jakarta
Abstrak: Polycarbonate (PC) has become one of the most popular choice as acontainer/food packaging plastic for baby milk bottles. This plastic is made by bisphenol-A (BPA) as a binder to improve plastic properties of a hard, clear, and light. However, behind the advantages, the reversed and the use of the polycarbonate as a raw material of bottle, stores hazard for human health. BPA is small molecule and carcinogenic. This compound is easily off or leach from the polymer matrix and then migrate to the food package. The study was conducted to determine the value of the average daily intake of BPA from baby milk bottle made from PC in Jakarta capital area. The Babies are in the zero month until three years old. It was also to estimate exposure value of the bisphenol-A and compared it with the value of the TDI (Tolerable Daily Intake). The data of food consumption, chemical level in food and baby weight were obtained by respondent survey in food consumption. Furthermore, all three of these data were used as the basis for exposure calculation. This value and then was evaluated against TDI. This study resulted on estimated value of exposure of the population was 0.0023 mg bisphenol-A/body weight/day. This number is still less than TDI (Tolerable Daily Intake) allowed by Food and Drugs Administration U.S (FDA) as much as 0.05 mg polycarbonate/body weight/day.
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Judul: Kajian Risiko Bisfenol A dari Kemasan Makanan Kaleng.
Abstrak: Bisfenol A merupakan senyawa kimia sintetik yang dapat mengganggu sistem endokrin. Sumber utama paparan bisfenol A pada manusia adalah melalui makanan dan minuman yang sudah kontak dengan plastik polikarbonat atau epoksi resin. Bisfenol A dalam bentuk epoksi resin biasanya digunakan sebagai enamel atau pelapis kemasan makanan kaleng. Bisfenol A mempunyai risiko mengalami migrasi dari kemasan ke makanan. Kajian risiko dilakukan untuk memperkirakan tingkat risiko bisfenol A dari makanan kaleng. Kajian risiko dalam penelitian ini dilakukan dengan studi pustaka mengenai bahaya dan risiko dari bisfenol A, survei konsumsi makanan kaleng dengan metode wawancara menggunakan food frequency questionaire (FFQ) di Jakarta Selatan dan Jakarta Utara, tabulasi data survei dari 6 provinsi di Indonesia, penentuan konsentrasi migrasi bisfenol A yang digunakan untuk perhitungan paparan, dan analisis data. Hasil survei menunjukan bahwa jenis makanan kaleng yang paling banyak dikonsumsi oleh responden adalah susu sterilisasi siap minum, susu kental manis, dan ikan. Karakteristik responden dengan rata-rata asupan makanan kaleng yang relatif tinggi adalah responden yang memiliki pekerjaan wiraswasta, pendidikan formal sarjana, usia 26-45 tahun, jenis kelamin laki-laki dan berat badan relatif gemuk. Hasil estimasi paparan menunjukan bahwa nilai persentil ke-90 paparan bisfenol A adalah 9.31 x mg/kg BB/ hari yang masih jauh dibawah TDI.
Keyword: bisfenol A, enamel, kajian risiko, makanan kaleng, migrasi

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