Judul: Analisis Strategi Bisnis Obat-Obatan Tradisional Studi Kasus di PT. Indofarma (Persero), Jakarta
Abstrak: PT. Indofarma (persero) adalah badan usaha milik negara yang bergerak di bidang farmasi. Perusahaan ini memproduksi obat-obatan modern dan peralatan kesehatan lainnya. Pada tahun 1996 PT. Indofarma (Persero) memproduksi obat-obatan tradisional dengan menggunakan teknologi modern.
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Judul: Analisis pemasaran obat tradisional: Studi kasus pada Koperasi Bhinneka Karya Manunggal, Bogor
Abstrak: Obat-obatan tradisional yang telah ada sejak dahulu merupakan altematif pengobatan pada saat ini yang dapat dijangkau oleh seluruh lapisan masyarakat. Dengan adanya peluang di atas maka jumlah perusahaan penghasif obat-obatan tradisional setiap tahunnya terns meningkat. Dengan semakin banyaknya perusahaan yang terjun dalam bisnis ini, maka persaingan antar perusahaan semakin ketat. Untuk memenangkan persaingan tersebut, salah satu aspek penting yang perlu diperhatikan adalah bidang pemasaran. Tujuan dari penelitian, yang dilakukan pada bulan Juli sampai Agustus 1997 ini adalah (1) Menganalisis strategi pemasaran produsen obat tradisional selama ini, (2) Mengidentifikasi dan menganalisis kekuatan, kelemahan, peluang serta ancaman dalam memasarkan produk obat tradisional, (3) Merumuskan beberapa altematif strategi pemasaran bagi produsen obat tradisional. Penelitian dilaksanakan pada bulan Juli hingga Agustus 1997. Analisis yang digunakan meliputi siklus hidup produk, peramalan penjualan dan bauran pemasaran untuk menunjukkan keragaan pemasaran produk serta analisis SWOT untuk menghasilkan altematif strategi pemasaran.
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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