Judul: Kajian Mutu Air Minum Pada Depo Air Minum Di Wilayah DKI Jakarta
Abstrak: Air marupakan kebutuhan manusia yang mutlsk harus dipenuhi dan FUngsinya tidak dapat digantikan oleh senyawa yang lain. Kandungan air dalam tubuh manusia rata-rata 65 % atau sekiar 47 liter pada orang dewasa. Setiap hari sekitar 2,51i1er air harus diganti dengan yang baru. Diperkirakan dari sejumlah air yang harus diganti teIsebut, 1,5 liter berasal dari air minum dan 1.0 liter berasal dari makanan yang dikonsumsi.
Keyword: 

Judul: Pola Konsumsi dan Faktor-Faktor yang Memengaruhi Konsumsi Air.
Abstrak: Kelurahan Kebayoran Lama Selatan merupakan salah satu wilayah di Jakarta Selatan yang masih mengandalkan air tanah sebagai sumber utama pemenuhan kebutuhan air sehari-hari. Keterbatasan layanan air PDAM menyebabkan masyarakat masih menggunakan air tanah. Tujuan penelitian ini adalah: 1) mengidentifikasi sumber dan pola konsumsi air, serta sumber air yang paling besar dikonsumsi; 2) mengidentifikasi persepsi masyarakat terhadap sumber air yang digunakan; 3) membandingkan persentase pengeluaran konsumsi air antara rumah tangga pengguna air tanah dengan rumah tangga pengguna air PDAM; 4) menganalisis faktor-faktor yang memengaruhi konsumsi air. Penelitian ini menggunakan analisis deskriptif, Skala Likert, analisis proporsi pengeluaran, dan regresi linear berganda. Hasil penelitian menunjukkan terdapat empat sumber air yang digunakan dan membentuk sembilan pola kombinasi penggunaan air. Air tanah merupakan sumber air dengan penggunaan yang paling besar. Analisis persepsi terhadap sumber air menunjukkan bahwa kualitas air PDAM lebih rendah dari air tanah dan air minum dalam kemasan (AMDK)/air isi ulang. Persentase pengeluaran konsumsi air rumah tangga pengguna air PDAM lebih tinggi dibandingkan dengan rumah tangga pengguna air tanah. Hasil analisis menunjukkan bahwa faktor-faktor yang berpengaruh terhadap konsumsi air adalah pendapatan, volume konsumsi air, dan pelanggan PDAM atau bukan pelanggan PDAM.
Keyword: pengeluaran konsumsi air, persepsi, volume

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