Judul: Pengaruh round-up dan fusilade sebagai senyawa pemacu kemasakan tanaman tebu terhadap produksi gula pada perkebunan tebu PT Perkebunan IX
Abstrak: Tujuan penelitian adalah untuk mengetahui pengaruh penggunaan Round-up dan fusilade dengan berbagai dosis perlakuan yang dikombinasikan dengan saat pemberian terhadap komponen produksi (Rendemen, Hablur, Bobot, Kemasakan, Kosien Peningkatan, Kosien Daya Tahan, Hasil bagi kemurnian, Nilai Nira, Brix, Pol, Tinggi tanaman, Diameter batang dan Jumlah ruas).
Keyword: round-up, fusilade

Judul: Pengaruh Pupuk Nitrogen dan Fosfor Terhadap Pertumbuhan dan Produksi Tebu (Saccharum officinarum L.)
Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh pemupukan Nitrogen dan Fosfor terhadap pertumbuhan dan produksi tebu. Penelitian ini dilaksanakan pada bulan Februari 2009 sampai Agustus 2009 yang berlokasi di Rayon II Afdeling 7 Kebun Bungamayang PTPN VII (Persero) Kotabumi, Kabupaten Lampung Utara. Penelitian ini menggunakan bahan tanaman tebu varietas Kidang Kencana (BM 9605) yang sudah ditanam sejak bulan Agustus 2008. Model rancangan penelitian menggunakan Rancangan Acak Kelompok. Perlakuan yang digunakan terdiri atas dua faktor. Faktor pertama adalah taraf pemupukan Nitrogen yang terdiri atas 90, 135, 180, dan 225 kg N/ha. Faktor kedua adalah taraf pemupukan Fosfor yang terdiri atas 36, 72, 108, dan 144 kg P/ha. Tiap petak percobaan dipupuk K2O dengan dosis 270 kg/ha. Percobaan terdiri atas 16 kombinasi perlakuan yang diulang sebanyak 3 kali sehingga terdapat 48 satuan percobaan. Setiap satuan percobaan terdiri atas 10 juring dengan jarak pusat ke pusat (pkp) 1.3 m dan setiap juring ditanam 90 stek. Setiap satuan percobaan terdiri dari 3 rumpun contoh yang diamati. Variabel-variabel yang diamati terdiri atas jumlah anakan per rumpun, tinggi batang, diameter batang, jumlah ruas, jumlah daun per tanaman, jumlah tanaman per juring, bobot kering organ tanaman, rendemen, jumlah tanaman dipanen per juring, luas daun spesifik, analisis hara tanaman, peubah parameter tanah dan analisis hara tanah.
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