Judul: Keragaman Genus Fungi pada Tanah Hutan Mangrove Tercemar Logam Berat di Muara Angke, DKI Jakarta
Abstrak: Vegetasi mangrove merupakan vegetasi yang cenderung mengakumulasi logam-Iogam berat yang terdapat pada ekosistem yang bersangkutan. Hal ini tidak lepas dari peranan mikroba-mikroba tanah yang membantu tanaman untuk mengakumulasi logam-logam berat tersebut, baik mikroba yang mengkonsumsi logam itu sendiri ataupun mikroba yang bersatu dengan jenis tanaman tertentu untuk mengakumulasi logam berat tersebut. Semakin bertambahnya kegiatan industri telah menyebabkan semakin banyaknya jumlah limbah yang dihasilkan. Limbah industri ini menimbulkan masalah yang serius bagi ekosistem perairan karena menurunkan kualitas air yang akan berdampak pada ekosistem mangrove. Kegiatan-kegiatan tertentu telah menghasilkan limbah logam berat khususnya Hg, Pb dan Cu. Limbah logam berat yang tidak diolah masuk perairan laut dan mengalami pengendapan, pengenceran, dispersi dan metilasi oleh aktivitas mikroba dan selanjutnya akan diserap oleh organisme di perairan tersebut.
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Judul: Akumulasi logam berat (Mn, Zn, Cu.) pada jenis Rhizophora mucronata di hutan tanaman mangrove RKPH Cilacap BKPH Rawa Timur KPH Banyumas Barat, Perum Perhutani Unit I Jawa Tengah
Abstrak: Untuk menunjang pembangunan, banyak industri-industri dibangun tidak hanya di daerah industri tetapi juga di daerah pantai/teluk seperti halnya di Cilacap (pabrik se- men, pupuk, kilang minyak). Limbah yang dikeluarkan sudah tentu dapat berdampak pada lingkungan terutama jika menge- luarkan logam-logam berat. Akumulasi logam berat pada vegetasi mangrove dapat digunakan untuk mendeteksi akumulasi logam berat di eko- sistem tersebut. Penelitian ini dilakukan di Hutan Tanaman mangrove Cilacap dan analisis akumulasi logam berat dilakukan di Laboratorium Balai Penelitian dan Pengembangan Tanaman Pangan Bogor. Survey lapangan dilaksanakan pada bulan April 1994. Pengambilan contoh dengan cara komposit pada tiap-tiap lokasi pengamatan yang terdiri dari tiga kelom- pok (0-300 m, 600 900 m, 1200-1500 m menjauhi pabrik). Hasil penelitian menunjukkan bahwa akumulasi terba- nyak logam Mn di ketiga kelompok terjadi pada bagian daun (181.1 ppm, 187.4 ppm, 174.3 ppm). Akumulasi logam Zn terbanyak di kelompok I pada bagian akar (11.2 ppm), di kelompok II pada daun (7.6 ppm) dan di kelompok III pada bunga/buah (17 ppm). Sedangkan akumulasi logam Cu terba- nyak di ketiga kelompok terjadi pada akar (24.2 ppm, 5.5 ppm, 18.4 ppm). Dari ketiga kelompok pengamatan, akumulasi terbanyak tiap logam berat bervariasi. Logam Mn lebih banyak tera- kumulasi di kelompok II (357.4 ppm), logam Zn di kelompok III (36.6 ppm) dan logam Cu di kelompok I (349.7 ppm)....
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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