Judul: Analisis laporan keuangan parsial PT Kerja Niaga sebagai penyangga dan pemegang stok nasional cengkeh studi kasus di PT Kerta Niaga, Jakarta Barat
Abstrak: Cengkeh merupakan salah satu komoditi penting yang sebagian besar dihasilkan petani dan merupakan salah satu bahan baku bagi industri pabrik rokok kretek. Dengan demikian kelangsungan pengadaan cengkeh dan kemantapan harga cengkeh perlu dijamin. Keadaan harga cengkeh di tingkat petani yang berfluktuasi dan cenderung menurun, akan berakibat buruk terhadap peningkatan pendapatan dan kesejahteraan petani produsen cengkeh. Akibat buruk lain yang ditimbulkan adalah intensif petani kurang untuk meningkatkan produksi cengkeh per hektar.
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Judul: Studi perbandingan antara komoditas teh dan cengkeh ditinjau dari aspek finansial : studi kasus di PTP XII Perkebunan Pasir Nangka, Cianjur
Abstrak: Praktek lapangan ini merupakan studi kasus pada PTP duabelas Perkebunan Pasir Nangka, yang terletak di Kabu- paten Cianjur (Jawa Barat) dan dilaksanakan selama dua bulan, yaitu mulai Bulan Desember 1987 s/d Januari 1988. Tujuan Praktek lapang adalah untuk; (1) Mengetahui keadaan umum Perkebunan Pasir Nangka (2) Mengadakan studi komparatif antara komoditas teh dan cengkeh ditinjau dari aspek finansial, sehingga diketahui; (a) profitabilitas dalam perhitungan NPV (b) produktivitas dalam perhitungan IRR (c) likwiditas dan solvabilitas dalam perhitungan E, CV dan L. Dalam praktek lapang ini digunakan data selama 16 tahun yaitu data tahun 1971 s/d 1986, yang terdiri dari data primer dan data sekunder. Untuk cengkeh, yaitu data tahun tanam 1971 s/d 1975, sedang untuk teh adalah data tahun tanam 1971 s/d 1980. Kedua komoditas ini diperbandingkan berdasarkan satu luasan yang sama yaitu satu ha. Produk si rata-rata per ha per tahun berkisar antara 970 kg s/d 2 267 kilogram untuk teh dan 24.05 kg s/d 193.25 kg untuk bunga cengkeh, sedang untuk tangkai cengkeh berkisar antara 8.16 kilogram s/d 77.47 kg...
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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