Judul: Tingkat Konsumsi Energi dan Zat Besi (Fe), Status Gizi dan Produktivitas Kerja Karyawan pada Bagian Produksi PT Air Mancur Palur, Karanganyar
Abstrak: Energy and iron (Fe) are nutrients that have important contribution in supporting the productivity of manpower. Energy as the source of the main power. In the meantime, the iron deficiency could result in reduce the productivity and physical capacity. The purpose of this research is to know the level of energy and iron consumption, nutritional status and productivity of the employee at production part of PT Air Mancur Palur, Karanganyar. Design of this research is Cross Sectional Study. Data is carri out at June 2009 in PT Air Mancur Palur, Karanganyar. Sample in this research is 80 employee at the production part. Method of the data collection is by questionnaire. Data processing and analysis is carri out descriptively and by using Microsoft Office Excel 2007 and SPSS 17. Level of energy consumption of 38,75% samples are normal (TKE 90-119%) and 36.25% samples are more (TKE 120%). Level of iron consumption of 66,25% samples are normal (TK 77%). Nutritional status of 60% samples are normal (BMI 18.50-24.99) and 31,25% samples are overweight (BMI 25.00). Productivity is measure by the number that produce in a day (output/day). The number of 48.75% samples produce output/day above in general the group, 32,5% samples are below in general and 18.75% samples produce output/day is same as general the group. In the meantime, the number of 63.75% samples always be present at work for the last month. Keywords: energy consumption, iron consumption, productivity
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Judul: Konsumsi Pangan, Status Gizi dan Produkstivitas Kerja Karyawati Pabrik Garment (Studi Kasus di PT Truba Raya Trading, Kecamatan Ciawi, Kabupaten Bogor, Propinsi Jawa Barat)
Abstrak: Penelitian dilaksanakan di PT TRUBA Raya Trading Gartex Division (TRUBA Gartex), Kecamatan Ciawi, Kabupaten Bogor, dari bulan Agustus sampai Oktober 1992. Contoh yang diteliti adalah karyawati yang berstatus borongan bagian jahit, sebanyak 61 orang. Data yang dikumpulkan terdiri dari data primer dan data sekunder. Data primer meliputi keadaan umum contoh, besar keluarga, pendapatan rata-rata, riwayat kesehatan, konsumsi pangan, berat badan, tinggi badan, kadar hemoglobin dan produktivitas kerja, yang diperoleh dengan cara wawancara dan pengukuran langsung. Data sekunder meliputi keadaan umum karyawan, peraturan kerja, sistem upah, daftar absensi dan jaminan sosial. Untuk mengetahui ada tidaknya hubungan antara tingkat konsumsi zat besi dengan kadar hemoglobin, hubungan antara konsumsi energi dan protein dengan produktivitas kerja, dan hubungan antara status gizi (secara antropometri dan kadar hemoglobin) dengan peroduktivitas kerja digunakan uji Chi-Kuadrat (Siegel, 1985). Penelitan menghasilkan rata-rata konsumsi energi 1366 kkal, protein 35,5 g, vitamin C 34,4 mg dan zat besi 6,3 mg, dimana konsumsi energi sebesar 495 kkal, protein 12,6 g, vitamin C 13,9 mg dan zat besi 4,5 mg berasal dari makanan yang disediakan.oleh perusahaan, sedangkan sisanya berasal dari sumber lain.
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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