Judul: Periphyton Community Structure as a Bioindicator of Water Pollution in the Cibareno River, Sukabumi, West Java
Abstrak: Aktivitas antropogenik di sekitar Sungai Cibareno menyebabkan bertambahnya buangan limbah organik dan anorganik yang tersebar di sepanjang aliran sungai, sehingga kualitas perairan mengalami penurunan. Pemantauan kualitas air dapat dilakukan menggunakan indikator biologi seperti perifiton. Penelitian ini bertujuan untuk menganalisis kondisi perairan Sungai Cibareno berdasarkan struktur komunitas perifiton. Metode penentuan lokasi pengamatan yang digunakan adalah purposive sampling. Pengambilan contoh air dan perifiton dilakukan di enam stasiun dan setiap stasiun dilakukan tiga kali pengulangan. Identifikasi dan klasifikasi perifiton dilakukan berdasarkan genus. Parameter kualitas air yang dianalisis meliputi parameter fisika kimia. Analisis penentuan kualitas perairan menggunakan indeks saprobik. Hasil analisis menunjukkan struktur komunitas perifiton di perairan tersebut terdiri dari empat kelas. Jumlah jenis dan kelimpahan perifiton didominasi oleh Bacillariophyceae dari genus Navicula dan Nitzschia. Keanekaragaman perifiton di Sungai Cibareno tergolong sedang dan komunitas stabil. Model persamaan regresi linier yang didapatkan menunjukkan terdapat hubungan positif antara parameter kecerahan dan Dissolved Inorganic Nitrogen (DIN) terhadap kelimpahan total perifiton. Nilai saprobik berkisar 0,63­1,10 (β Meso/oligosaprobik) yang menunjukkan bahwa sungai telah tercemar ringan oleh bahan organik dan anorganik., Anthropogenic activities around the Cibareno River cause an increase in the discharge of organic and inorganic waste scattered along the river flow, so that the quality of the waters has decreased. Water quality monitoring can be carried out using biological indicators such as perifiton. This study aims to analyze the condition of the waters of the Cibareno River based on the structure of the perifiton community. The method of determining the observation location used is purposive sampling. Water and perifiton sampling was carried out at six stations and each station was carried out three repetitions. Identification and classification of periphytons is carried out by genus. The analyzed water quality parameters include chemical physics parameters. Analysis of water quality determination using saprobic index. The results of the analysis showed that the structure of periphyton communities in these waters consisted of four classes. The number of species and abundance of periphytons is dominated by Bacillariophyceae of the genera Navicula and Nitzschia. The periphyton diversity in the Cibareno River is moderate and the community is stable. The linear regression equation model obtained shows a positive relationship between the brightness parameter and Dissolved Inorganic Nitrogen (DIN) to the total abundance of perifiton. The saprobic value ranges from 0.631.10 (β Meso/oligosaprobic) which indicates that the river has been lightly polluted by organic and anorganic matter.
Keyword: saprobiotic index, biological indicator, periphyton, Cibareno River

Judul: Pengaruh Unsur Hara (N Dan P) Terhadap Biomassa Dan Struktur Komunitas Perifiton Studi Kasus Sungai Ciliwung
Abstrak: Research on the effect of nutrient to the structure of periphyton communities in Ciliwung river has been conducted from December 2010 to May 2011 at four stations; Gn. Mas, Kp. Pensiunan, Kp. Jogjogan, and Cibinong which reflected the of input of anthropogenic pollutant. This study aims to determine the relationship between nutrients (N and P) concentration and the structure changes of periphyton community in order to determine the ecological condition of Ciliwung River. The results of this study are expected to be useful to make a policy in the management of ecological disturbance of Ciliwung River based on pollutants loads and environmental changes due antropogenic activity. Water quality Ciliwung River was evaluated from the condition of habitats, pollution levels and the conditions of periphyton integrity to observed the actual condition of the aquatic environment. The results showed optimal habitat conditions was observed in Gn. Mas while other stations condition were marginal (Kp. Pensiunan, Kp. Jogjogan and Cibinong). Based on pollution level category, Gn. Mas and Kp. Pensiunan was unpolluted, while Kp. Jogjogan and Cibinong was slightly polluted and moderately polluted respectively. The results obtained 83 species of periphyton consisted of Bacillariophyceae (44 species), Chlorophyceae (20 species), Cyanophyceae (14 species), Rhodophyceae (1 species), Xantophyceae (2 species) and Dinophyceae (2 species). Based on the abundance of periphyton, PIBI score obtained was almost the same Gn. Mas (95,97), Kp. Pensiunan (84,65), Kp. Jogjogan (93,57) and Cibinong (83,83). CCA ordination of the results obtained a clear grouping among the research station. While the results from a combination of habitat conditions, the level of pollution and its PIBI value confirm that water conditions are still good.
Keyword: 

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