Judul: Analisis Situasi Ketahanan Pangan dan Gizi Kota Tangerang Periode Tahun 2008-2011
Abstrak: The study is aimed to analyze food and nutrition security of Tangerang City consisted of food supply, distribution, consumption, and nutritional status during the period of 2008-2011.In common, Tangerang City food supply equal to energy in the period of 2008-2011 was fulfill the WNPG recommended dietary allowance, however its decrease in the latest year. Despite of no food storage held by the local government of Tangerang City yet, BULOG Sub Divre Tangerang manage government rice stock that can be used by local government whenever needed to be released in the market during rice shortage. In general food distribution in Tangerang city is stable as indicated by low coefficient of variance of desicable food price. Quality of food consumption is remained a serious problem since the dietary pattern score (PPH score) in 2011 was only 77.3 and energy adequacy level 97.70%. Local government survey found that 33.3 % of selected food marketed were not comply the regulation regarding uses of hazardous subtances added to food such as borax, formalin and textile colorant. Under nutrition prevalence reach 12.6% which was lower than MDG’s target of 18.5% in 2015, but in some villages under nutrition are still prevalent an the prevalence was higher than MDG’s target
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Judul: Analisis Situasi Ketahanan Pangan serta Hubungannya dengan Prevalensi Stunting di Provinsi Banten
Abstrak: Penelitian ini bertujuan menganalisis situasi ketahanan pangan serta menganalisis hubungannya dengan prevalensi stunting di Provinsi Banten. Data yang digunakan yaitu data sekunder dengan unit analisis 8 kabupaten/kota di Provinsi Banten tahun 2017 dan 2018. Tingkat ketersediaan energi dan protein tidak memenuhi Standar Pelayanan Minimal (SPM) (<90%) dan skor Pola Pangan Harapan (PPH) ketersediaan tidak memenuhi skor ideal (<100). Tingkat kemiskinan lebih tinggi dari target. Proporsi persentase pengeluaran pangan per kapita penduduk lebih besar daripada pengeluaran non pangan. Tingkat kecukupan energi dan protein sudah memenuhi SPM (>90%). Namun, skor PPH konsumsi belum memenuhi skor ideal (<100). Rata-rata lama sekolah perempuan yaitu setara dengan SMP. Angka Harapan Hidup (AHH) lebih rendah dari skor nasional (<71 tahun). Prevalensi stunting tahun 2017 tergolong tinggi (>29%) sedangkan pada tahun 2018 tergolong rendah (≤29%). Terdapat hubungan signifikan searah (p<0.05) antara tingkat ketersediaan energi dan protein, skor PPH ketersediaan, tingkat kemiskinan, dan pengeluaran pangan per kapita dengan prevalensi stunting. Terdapat hubungan signifikan yang tidak searah (p<0,05) antara tingkat kecukupan protein, skor PPH konsumsi, rata-rata lama sekolah perempuan, dan AHH dengan prevalensi stunting. Terdapat hubungan tidak signifikan (p>0,05) antara tingkat kecukupan energi dengan prevalensi stunting.
Keyword: Banten Province, food security situation, stunting prevalence

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