Judul: Masker Chitosan Polymer Medium Pereduksi Asap Rokok Dan Emisi Kendaraan Bermotor
Abstrak: Masker merupakan pelindung mulut dan hidung dari gas polutan termasuk asap rokok dan emisi kendaraan bermotor. Chitosan polymer medium (CPM) merupakan salah satu bentuk turunan kitosan, diperoleh dengan cara pengecilan polimer besar menggunakan magnetic stirrer. Tujuan dari penelitian ini adalah untuk mengetahui efektivitas chitosan polymer medium sebagai pereduksi terhadap asap rokok dan emisi kendaraan bermotor. Fokus penelitian pada perlakuan CPM, yakni CPM 0%, 0,5% dan 1%. Hasil penelitian menunjukan kadar piridin dan nikotin berkurang sebanyak 5,8% pada CPM 0,5% dan 10,4% pada CPM 1%, sedangkan bisoflex dapat berkurang sebesar 1,0% pada CPM 0,5%. Kadar heksametil menurun 4,5% pada CPM 0,5%, kadar benzoxazol efektif berkurang 1,6% pada CPM 0,5%, dan kadar karbonil berkurang 0,4% pada CPM 0,5% juga berkurang 1,0% pada CPM 1%. Konsentrasi terbaik CPM 1% efektif dapat menurunkan kadar piridin, nikotin dan karbonil.
Keyword: kitosan, magnetik stirer, masker, pereduksi, polimer.

Judul: Analisis Efektivitas Masker dalam Menyaring Asap, Total Suspended Particulate, Debu Jatuh, dan Intensitas Kebauan
Abstrak: Saat ini terdapat beberapa masker yang tidak efektif saat digunakan. Oleh karena itu, dibutuhkan penelitian yang menganalisis efektivitas masker yang biasa digunakan masyarakat dalam kehidupan sehari-hari. Tujuan dari penelitian ini adalah menganalisis efektivitas masker dalam menyaring asap, TSP (Total Suspended Particulate), debu jatuh, dan intensitas kebauan, menentukan masker terbaik berdasarkan tujuh masker yang diuji, serta menganalisis ukuran pori lapisan penyaring masker. Hasil analisis menunjukkan tidak semua masker yang diuji memiliki nilai efektivitas yang sama pada setiap parameter uji. Efektivitas rata-rata masker dalam menyaring asap sebesar 77%, TSP sebesar 57%, debu jatuh sebesar 22%, dan intensitas kebauan sebesar 77% dan dari keseluruhan parameter sebesar 58% . Masker terbaik dalam mereduksi semua parameter yang diuji adalah masker tipe D. Ukuran pori masker memiliki nilai yang beragam yaitu rentang nilai 200.62-387.09 μm untuk lapisan pertama, 43.28-391.84 μm untuk lapisan kedua, dan 172.63-379.99 μm lapisan ketiga.Perbedaan efektivitas masker tersebut dapat dikarenakan material filter, bentuk, dan jumlah filter masker yang berbeda-beda.
Keyword: asap, debu jatuh, efektivitas masker, kebauan, Total Suspended Particulate

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