Judul: Analisis Jenis, Jumlah, dan Mutu Gizi Konsumsi Sarapan Anak Indonesia
Abstrak: The objective of this study was to analyze type, amount, and nutritional quality of breakfast among Indonesian children aged 3-12 years old. The data used for this study was the secondary data of Basic Health Survey 2010 (Riskesdas 2010) conducted by the Research and Development Agency, Ministry of Health Indonesia. Data was collected June until August 2010 by applying a cross sectional study design. This study covered 33 provinces of Indonesia, with 40 437 final total subjects; children consist of 20 659 boys and 19 778 girls. The results of this study showed that the ten major type of foods consumed during breakfast were rice, swamp cabbage, egg, fish, tempe, instant noodles, tofu, bread, chicken and biscuits; and the five major type of beverages consumed during breakfast were drinking water, tea, milk, coffee, and syrup. The food consumed on average of more than 5 g a day during breakfast were rice, swamp cabbage, egg, fish, tempe, instant noodles; and the beverages consumed on average of more than 15 mL a day were water, tea, and milk. Only 30.3% of children breakfast adequately fullfilled energy intake. The results showed that there was a positive significant correlation between parental education and family economic status with contribution of breakfast energy and nutritional quality of breakfast (p<0.01).
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Judul: Analisis jenis dan jumlah serta mutu gizi sarapan pada anak usia sekolah perkotaan dan perdesaan di Indonesia
Abstrak: Anak usia sekolah merupakan bagian dari generasi dan investasi bangsa, maka upaya peningkatan kualitas sumber daya manusia harus dilakukan sejak masa anak. Anak usia sekolah memerlukan asupan gizi yang baik sepanjang hari, salah satunya adalah sarapan yang diperlukan untuk menunjang kegiatan belajar dan aktivitas lainnya. Tujuan penelitian ini adalah menganalisis jenis dan jumlah pangan sarapan serta mutu gizi sarapan anak usia sekolah (6-12 tahun) perkotaan dan perdesaan di Indonesia. Konsumsi makanan dan minuman anak selama sarapan diperoleh dari data hasil recall individu 24 jam hasil penelitian Studi Diet Total Kementrian Kesehatan, 2014. Asupan gizi dihitung berdasarkan data konsumsi pangan dan kandungan gizi pangan. Total subjek pada penelitian ini adalah 25 935 anak. Hasil dari penelitian ini menunjukkan sepuluh jenis makanan yang populer dikonsumsi sebagai sarapan anak usia sekolah adalah nasi, telur, ikan, tempe, mie instan, daging ayam, biskuit, tahu, roti dan wortel; serta lima jenis minuman yang populer dikonsumsi anak usia sekolah adalah air putih, teh, susu, sirup dan kopi. Konsumsi telur, tempe, mi instan, daging ayam, biskuit, tahu, roti, wortel, teh dan susu lebih populer di perkotaan sementara konsumsi nasi, ikan, air putih, sirup dan kopi lebih populer di perdesaan. Hampir setengah (47.7%) anak usia sekolah belum memenuhi kebutuhan energi sarapan, yaitu asupan energi sarapan kurang dari 15% kebutuhan harian. Lebih dari tiga-perempat anak (79.8%) masih mengkonsumsi sarapan dengan mutu gizi yang rendah. Lebih banyak anak usia sekolah yang memenuhi kebutuhan energi dan zat gizi sarapan di perkotaaan dibanding diperdesaan.
Keyword: Anak usia sekolah, mutu gizi sarapan, perdesaan, perkotaan, studi diet total.

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