Judul: Analisis Asupan Asam Folat, Vitamin B12 dan Vitamin C pada Ibu Hamil di Indonesia berdasarkan Studi Diet Total
Abstrak: Kebutuhan vitamin meningkat saat kehamilan. Asam Folat, vitamin B12 dan vitamin Csangat dibutuhkan untuk mencegah terjadinya anemia dan risiko lainnya. Penelitian ini bertujuan untuk menganalisis asupan vitamin (asam folat, vitamin B12 dan vitamin C) pada ibu hamil di Indonesia berdasarkan Studi Diet Total. Penelitan ini menggunakan data sekunder Studi Diet Total (SDT) yang didesain dengan cross-sectional study. Data konsumsi diperoleh dari hasil recall individu 24 jam. Asam folat, vitamin B12 dan vitamin C dianalisis menggunakan USDA, DKBM, nutrisurvey dan nutritionfact. Rata-rata asupan asam folat, vitamin B12 dan vitamin C berturut-turut 152.4±98.7μg/hr, 3.4±7.1 μg/hr dan 62.3±72.7 mg/hr. Prevalensi subjek yang tergolong defisiensi tingkat berat untuk asupan asam folat, vitamin B12 dan vitamin C berturut-turut adalah 88.3%, 34.5% dan 46.9%. Hasil analisi regresi logistik menunjukkan bahwa faktor risiko sosial-ekonomi terhadap defisiensi asam folat adalah umur dan status ekonomi; untuk defisiensi vitamin B12 adalah tingkat pendidikan dan status ekonomi; dan untuk vitamin C adalah tingkat pendidikan.
Keyword: Asam folat, Ibu hamil, Vitamin B12, Vitamin C

Judul: Analisis Asupan Zat Gizi Mikro dan Hubungannya dengan Status Gizi pada Ibu Hamil di Wilayah Bogor
Abstrak: Konsumsi makanan yang memenuhi kebutuhan gizi merupakan salah satu caranya faktor yang harus diperhatikan sebelum dan selama kehamilan. Kekurangan zat besi adalah kekurangan gizi yang paling umum dan paling luas di dunia. Untuk mencatat serta asupan mikronutrien seperti vitamin yang dapat meningkatkan status zat besi wanita hamil. Penelitian ini berdasarkan data yang dihasilkan dari Studi Gizi Status dan Pola Makan Ibu Pra Hamil (pada usia subur), Ibu Hamil dan Menyusui dilaksanakan oleh SEAFAST Center IPB. Itu Penelitian dilakukan di wilayah Bogor yang meliputi enam kecamatan. Subjek adalah ibu hamil yang pemeriksaan hemoglobin dan ferritinnya berjumlah 45 orang kehamilan trimester II. Variabel yang mempunyai korelasi nyata positif dengan kadar feritin berdasarkan Korelasi Pearson adalah vitamin A (r=0,415; p<0,05), vitamin B12 (r=0,402; p<0,05), dan asupan vitamin C (r=0,356; p<0,05). Asupan vitamin B12 memiliki pengaruh paling kuat terhadap kadar feritin dengan persamaan regresi Ferritin = -3,851+10.931 vitamin B12. Ada hubungan nyata yang negatif antara asam folat asupan dan kadar feritin (r =-0,355; p<0,05).
Keyword: Pregnant women, Micronutrient intake, Ferritin

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