Judul: Penetapan Harga Pokok Pucuk dan Teh Olahan Pada Perusahaan Teh Hitam Studi Kasus Perkebunan Malabar PTP XIII, kecamatan Pangalengan, Kabupaten Bandung
Abstrak: Tujuan penelitian ini adalah mempelajari struktur biaya perusahaan perkebunan teh hitam, menentukan harga pokok pucuk dan teh hitam serta menghitung titik impasnya. Penelitian di lapang dilakukan untuk tanaman yang sudah berproduksi (tanaman menghasilkan) dan penelitian menggunakan metoda akuntansi.
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Judul: Analisis finansial teh hitam : studi kasus di Perkebunan Papandayan PT Perkebunan XIII Garut, Jawa Barat
Abstrak: Perkebunan teh Papandayan merupakan salah satu industri pengolahan teh hitam milik PTP XIII yang terletak di Garut, Jawa Barat. Dalam menjalankan aktifitas usahanya terdapat beberapa permasalahan yang dihadapi, diantaranya dalam hal manajemen finansial, perkebunan Papandayan belum mampu menekan biaya produksi dan harga pokok, sementara itu harga jual teh hitam di pasaran Internasional selama beberapa tahun terakhir terus mero- sot. Tujuan penulisan Laporan Praktek Lapang ini adalah menganalisis keadaan biaya produksi selama 5 tahun ter- akhir (1981 sampai 1985) dengan mengidentifikasi dan menghitung komponen biaya produksi pada setiap departemen, menganalisis perkembangan harga pokok pucuk teh basah dan teh kering (teh hitam), menganalisis perkembangan rugi laba, mempelajari faktor-faktor penyebab kenaikan biaya produksi dan menyarankan usaha-usaha yang harus dilakukan untuk menekan/mempertahankan biaya produksi dan harga pokok teh hitam tersebut. Untuk menganalisis biaya produksi, harga pokok dan rugi laba, digunakan metoda akuntansi biaya. Hasil analisis biaya menunjukkan bahwa selama ре- riode 1981 sampai 1985, biaya produksi di departemen produksi basah meningkat rata-rata 7.8 persen, biaya produksi di departemen produksi kering meningkat rata- rata 9.1 persen, biaya produksi di departemen pembantu administrasi meningkat rata-rata 7.2 persen, sedangkan biaya produksi di departemen pembantu teknik menurun rata-rata 4.5 persen. Meningkat dan menurunnya biaya produksi di masing-masing departemen disebabkan oleh berbagai faktor, diantaranya adalah luas areal, jumlah tenaga kerja, tingkat harga bahan bakar minyak dan harga bahan penolong lainnya yang digunakan dalam proses produksi teh hitam...
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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