Judul: Persepsi masyarakat terhadap manfaat kesehatan dan pengembangan produk minuman fungsional dari ekstrak daun hantap (Sterculia oblongata R.Brown)
Abstrak: Indonesia is known by its diversity, especially ini herb-medicinal plants. The aims of this study was explore the health benefit and development of product of hantap leaves as functional drink by a community perception test. The study was conducted in April to December 2010. Study on product development was conducted at Laboratory of Food Processing, Laboratory of Organoleptic Test, and Laboratory of Food-Chemistry Analysis, Department of Community Nutrition- Faculty of Human Ecology, Bogor Agricultural University. Survey and perception test were conducted in sub district of Cicurug, Cidahu, and Parungkuda, district of Sukabumi. Respondent in this perception test study are 87 of men and women aged 20-60 years old and lived in resident of sub district of Cicurug, Cidahu, and Parungkuda, in district of Sukabumi,.
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Judul: Pengembangan Produk Minuman Jeli Ekstrak Daun Hantap (Sterculia oblongata R. Brown) sebagai Alternatif Pangan Fungsional
Abstrak: The objective of this study was to develop a jelly drink product based on hantap leaves extract as an alternative of functional food. Completed Randomize Nested Design with two factor (The type and level of concentration of the gelling agent) was applied in this study and resulted in nine formulas. The selected jelly drink formula was determined by preference test using semitrained panelists. Jelly drink with the addition of a gelling agent carrageenan with a concentration level of 0.20% and melon flavor was preferred by 86% panelist. This formula contained 87.37% water ,0.18% ash, 0.10% protein, 0 .04% fat, 12.3% carbohidrate, 2.08% fiber, 10.6 mg/100g total phenols, 0.68 mg/100g vitamin C and antioxidant activity 20.92 % with IC50 values is 464.02μL. With its bioactive component and fiber content, this product may be classified as functional food which may help improving consumer health.
Keyword: jelly drink., hantap leaves, functional food, fiber, antioxidants

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