Judul: Studi kelayakan pembangunan pabrik tablet effervercent jahe di kawasan PG Jatitujuh-Majalengka
Abstrak: Adanya kecenderungan pola hidup kembali ke alam (back to nature) menyebabkan masyarakat lebih memilih menggunakan obat atau minuman kesehatan alami yang diyakini tidak memiliki efek samping dan harga lebih terjangkau daripada obat atau minuman kesehatan sintetik. Kondisi ini memacu peningkatan kebutuhan akan obat tradisional maupun fitofarmaka. Pada tahun 1989 volume penjualan obat tradisional sebesar 970,6 ton, dan pada tahun 1998 terjadi peningkatan sekitar 10 kali lipat menjadi 9273,4 ton (Said, 2002). Tujuan penelitian ini adalah untuk mengetahui kelayakan pembangunan pabrik tablet effectescent jahe dikawasan PG Jatitujuh, Kabupaten Majalengka
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Judul: Analisis kelayakan industri tablet effervescent dari ekstrak temulawak (curcuma xanthorrhiza Roxb) di PT. Rajawali Nusantara Indonesia, Jakarta
Abstrak: Indonesia has a variety of medicinal herbs, which is around 11% of 20.000 worlds total medicinal herbs. Form 1994 to 1999, medicinal herbs export value growth has increased 24.33 %. The biggest export value is in 1997 with 22 million dollar. The average export volume increased 65.33% and the biggest is in 1999 i.e. 21.000 tons. Meanwhile, in 2000-2001, the world medicinal herbs increased up to 25 billion dollars. Unfortunatelly, most of the medicine herbs are as yet processed. Therefore, the studi to increase its added value is retrieved. One of the potential herbs that have potential to be developed is Temulawak (Curcuma xanthorriza Roxb)
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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