Judul: Kajian Mutu Minuman Susu Jahe Merah Dengan Kemasan Botol PET Selama Penyimpanan
Abstrak: Zingiber officinale Roscoe var. Rubrum or commonly known as red ginger is mostly used as herbal or medicinal products. UMKM Narasa is a home-based industry which is using the red ginger as the main composition of food product, that is red ginger milk beverage. The use of PET bottle for the packaging of red ginger milk beverage can help in extending the shelf life for 9 days. The quality microbiologically is determined in the total number of microbes for red ginger milk beverage by 6 x 102 colonies/ml. Proximate analysis showed the red ginger milk beverage consists of 84.73 % water, 0.46 % ash, 1.85 % fat, 0.54 % protein, and 12.42 % carbohydrate. The antioxidant activity using DPPH method showed the activity of antioxidant for red ginger milk beverage on its capabilty to reduce the free radical but in the high concentration. IC50 values of the red ginger milk beverage is 1142.08 mg/ml, this value can classify the activity of antioxidant in red ginger milk beverage as a very weak activity.
Keyword: Bogor Agricultural University (IPB), PET bottle, packaging, red ginger

Judul: Peningkatan Mutu Dan Penerapan Cara Produksi Pangan Yang Baik Pada Industri Rumah Tangga Pangan Minuman Jahe Merah Instan Di Desa Benteng, Ciampea, Bogor
Abstrak: Red ginger have been processed into several foods and beverages, such as instant beverage, ginger candy, ginger pickle, ginger coffee, etc. One of household industry that produces instant red ginger beverages is Jahe Gunung Leutik in Ciampea, Bogor. But, the household industry is still has not applying good manufacturing practices and it is still not has standard formula. Therefore, it is need a deep study to determine the standard formula and to apply manufacturing practices in order to get P-IRT certificate from health department. The methods that used in deciding the best formula are analysis of rehydration time, analysis of color, and hedonic test. The formula that used in the test was formula with ratio sugar and red ginger 1:2 (A), 1:1 (B), and 1:3 (C). After that, product from the best formula will be analyzed with proximate analysis in order to meet the requirement of P-IRT certificate’s submission. Moreover, feasibility analysis will be undertaken in this industry. The results showed that rehydration time in all three samples still include in instant beverages because its rapid rehydration time. Color analysis and hedonic test also showed no significant differences between the samples. Therefore, the formula with the ratio of 1:3 was chosen because it is the cheapest material usage. Moreover, Standard Operating Procedure (SOP) that controlled several aspect on industry from purchasing raw materials, production processes, until product shipment has been created according to the obtained formula. The best formula obtained from this experiment is analyzed its chemical composition and the results of moisture content, ash content, fat content, protein content and carbohydrate content are 1.16%, 1.17%, 0.08%, 0.46%, and 97.13% respectively. And after following several processed of certification, the household industry got the P-IRT number as follow 61232010110099. Feasibility analysis also undertaken by this household industry and the conclusion is this industry is feasible from the financial side.
Keyword: 

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