Judul: Karakteristik Sabun dengan Formula Tallow dan Ekstrak Temu Ireng (Curcuma aeruginosa) yang Berbeda
Abstrak: Tallow is a by-product that obtained from livestock production through fat rendering process. The high content of triglycerides in tallow can be utilized as raw bath soap with the saponification process. Temu ireng extract can be considered as fillers to the soap, because temu ireng extract countains higher total phenolic so that temu ireng can be acted as an antioxidants agent in the soap. The objective of this research was to study the characteristics of bath soap that made from different composition of tallow and extract temu ireng. Soap with A, B, and C formulation met the qualification with the SNI 06-3532-1994 in water content, the amount of fatty acid, and free alkaline, but did not to the amount of unsaponification fat. Soap with A, B, and C formula significantly affected the amount of fatty acids, pH value, unsaponifiable fat,and DPPH scavenging activity. The result of hedonic quality test from A, B, and C formula affected the intensity of color, temu ireng aroma, fatty aroma and foaming power significantly. DPPH scavenging activity had highest activity at 24.01% of C formula soap with antioxidant capacity of 73.47 mg EVC per 100 g and the amount of total phenolic was 17.32 mg GAE per 100 g.
Keyword: temu ireng (Curcuma aeruginosa), tallow, soap, Bogor Agricultural University (IPB)

Judul: Karakteristik Fisik Sabun Padat Berbahan Dasar Tallow dengan Penambahan Susu atau Krim
Abstrak: Animal fat generally have low economic value and less utilization. Animal fat can be processed into tallow through rendering process to produce a raw material in soap making. The purpose of this research was to analyze physical properties of soap by using tallow with milk or cream addition as raw material. The observed variables in this research were water content, hardness, pH, and foaming height. The randomized complete design with 4 treatments and 1 control was used as experimental design. Data were analyzed by analysis of variance (ANOVA). Kruskal Wallis test were used for nonparametric data. The results showed that water content of cream tallow soap and milk tallow soap had significant difference (P<0.05) with control soap. Hardness and foaming height of soap between treatments soaps and control soap had no significant difference. The value of pH of milk tallow soap had significant difference (P<0.05) with cream tallow soap and control. The organoleptic test results showed that cream tallow soap had significant difference (P<0.05) in colour with milk tallow soap. The cream tallow soap had no significant difference of favour with milk tallow soap. There was no significant difference on foaming ability between cream tallow soap and milk tallow soap.
Keyword: tallow, soap, physical properties

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