Judul: Model penyebaran kebisingan dan pengaruhnya terhadap pekerja. Studi kasus: PT. Wira Penta Kencana,  Kepulauan Riau
Abstrak: This research aims to determine sources and levels of noise; to develop in modelling; analyzing noise propagation, studying the impact of noise level to the employees; and to determine a set of proper noise control through working system and arrangement of noise source strategy
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Judul: Kajian Dampak Kebisingan (Dalam Lingkungan Pabrik) Terhadap Penurunan Tingkat Pendengaran Karyawan Di Kawasan Industri Kota Tangerang
Abstrak: Penurunan tingkat pendengaran adalah salah satu dampak negatif pencemaran lingkungan sebagai akibat dari intensitas suara dari mesin modern selama proses produksi. Kota Tangerang merupakan salah satu kawasan industri di Indonesia yang berpeluang menimbulkan pencemaran udara. Tujuan penelitian adalah mengukur tingkat kebisingan indoor dan mengidentifikasi tingkat gangguan pendengaran para karyawan, mengkaji variabel paling dominan yang berpengaruh pada penurunan tingkat pendengaran para karyawan, dan mengkaji bentuk keterkaitan antara kebisingan dan penurunan tingkat pendengaran. Variable eksternal yang berpengaruh pada penurunan tingkat pendengaran pada penelitian ini adalah umur, masa kerja, riwayat penyakit yang berhubungan dengan pendengaran (otitis media, hypertensi, trauma capitis, TBC, dan diabetes melitus), dan kebisingan tempat tinggal. Penelitian dilakukan pada Bulan April sampai dengan Mei 2006 di Kawasan Industri Kota Tangerang. Penelitian dilakukan dengan menggunakan metode observasi (expost facto) dengan pendekatan cross sectional. Industri terpilih dalam penelitian ini sebanyak 30 industri yang terdiri atas 8 industri pangan, 6 industri baja, 5 industri kayu/furniture, 3 industri kulit/sepatu, 4 industri tekstil, dan 4 industri plastik, dengan jumlah responden 300 orang. Berdasarkan hasil penelitian kebisingan tempat kerja yang melebihi nilai ambang batas yang ditetapkan (85 db) adalah industri baja mencapai 96,02 db, industri tekstil mencapai 88,13 db, dan industri kayu/furniture mencapai 88,12 db. Faktor dominan utama yang berpengaruh pada penurunan tingkat pendengaran karyawan adalah kebisingan tempat tinggal, penyakit, umur (industri pangan), masa kerja (industri baja dan kayu/furniture), kebisingan tempat tinggal dan penyakit (industri kulit/sepatu), umur (industri tekstil), dan penyakit (industri plastik). Berdasarkan hasil analisis spearman correlation, penurunan tingkat pendengaran karyawan berkorelasi positif nyata dengan umur, masa kerja, penggunaan alat pelindung telinga dan riwayat penyakit yang berhubungan dengan pendengaran karyawan (otitis media, hypertensi, trauma capitis, TBC, dan diabetes melitus).
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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