Judul: Evaluasi Kenyamanan Lingkungan Fisik Kerja pada Ruang Kuliah dan Laboratorium di Fakultas Teknologi Pertanian, Institut Pertanian Bogor
Abstrak: Kualitas lingkungan kerja fisik seperti pencahayaan, suhu dan kelembaban, dan tingkat kebisingan di Fakultas Teknologi Pertanian (Fateta), belum diketahui kesesuaiannya dengan standar yang berlaku. Tujuan dari penelitian ini adalah untuk mengetahui nilai parameter kenyamanan lingkungan fisik kerja dan menentukan ruang kuliah dan laboratorium di Fateta yang memenuhi standar KEP-48/MENLH/11/1996 dan SNI 03-6572-2001 serta analisis suhu berdasarkan grafik psikrometri. Tingkat kebisingan 16 jam tertinggi, suhu udara rata-rata tertinggi, dan intensitas pencahayaan rata-rata tertinggi berada di laboratorium Kimia Pangan dengan nilai berturut-turut 63.2 dB (A), 29°C dan 1076 lux. Kelembaban udara relatif rata-rata tertinggi berada di RK PAU 102B dengan nilai 84.1%. Berdasarkan parameter suhu dan tingkat kebisingan yang terukur, kenyamanan sebagian besar ruang kuliah dan laboratorium sesuai dengan standar yang berlaku. Namun kelembaban udara dan intensitas pencahayaan masih belum sesuai dengan standar kenyamanan yang berlaku.
Keyword: baku mutu, intensitas pencahayaan, kelembaban udara, suhu, tingkat kebisingan

Judul: Penentuan Indeks Kenyamanan Udara dalam Ruang Berdasarkan Temperatur, Kelembaban Relatif, Kebisingan, Kebauan dan Intensitas Cahaya
Abstrak: Beberapa penelitian menunjukkan bahwa bekerja dengan kondisi lingkungan yang baik akan meningkatkan produktivitas. Penelitian ini dilakukan untuk memformulasikan suatu indeks kenyamanan udara dalam ruang dengan mempertimbangkan kondisi temperatur, kelembaban relatif, kebisingan, kebauan, dan juga intensitas cahaya. Penelitian ini dilakukan dengan metode kualitatif dan kuantitatif. Pengukuran yang dilakukan antara lain: pengukuran temperatur, pengukuran tingkat kebisingan dan pengukuran intensitas cahaya, sedangkan untuk mengukur kesan bau digunakan skala hedonisme kebauan. Pembobotan dilakukan untuk mengetahui tingkat pengaruh dari masing-masing parameter berdasarkan 117 responden, dan diperoleh faktor pembobot sebesar 0.28 untuk temperatur, 0.16 untuk kelembaban relatif dan kebisingan, serta 0.20 untuk intensitas cahaya dan kebauan. Indeks kenyamanan udara dalam ruang ditetapkan 5 tingkatan, yakni tidak nyaman (1), kurang nyaman (2), cukup nyaman (3), nyaman (4), dan sangat nyaman (5). Berdasarkan hasil perhitungan, Lab. Lingkungan, ruang kuliah dan asrama mendapatkan indeks kenyamanan udara dalam ruang berkisar 2.3-2.9 (kurang nyaman), sedangkan Lab. Komputer sebesar 3.0 (cukup nyaman), serta UPT FATETA sebesar 3.4 (cukup nyaman).
Keyword: intensitas cahaya, kelembaban relatif, skala hedonisme, temperatur

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