Judul: Pendugaan Serapan Karbon Dioksida Pada Blok Rehabilitasi ConocoPhillips di Hutan Pendidikan Gunung Walat, Sukabumi.
Abstrak: Hutan memiliki peranan penting dalam upaya mengurangi emisi gas rumah kaca. Hutan mampu menyerap karbon dioksida dari atmosfer melalui proses fotosintesis dan menyimpannya dalam bentuk biomassa. Penelitian ini bertujuan menduga potensi serapan karbon dioksida pada blok rehabilitasi ConocoPhillips seluas 11.03 ha dalam rangka monitoring dan evaluasi tahunan pelaksanaan program rehabilitasi hutan yang dilaksanakan Hutan Pendidikan Gunung Walat bekerjasama dengan ConocoPhillips Indonesia Inc. Ltd. Penelitian dilakukan menggunakan metode penarikan contoh sistematis berlapis berdasarkan tahun tanam dengan intensitas contoh sebesar 15%. Pengambilan data dilakukan dengan mengukur diameter dan tinggi pohon pada plot contoh berbentuk lingkaran seluas 0.02 ha. Hasil penelitian menunjukan nilai dugaan serapan karbon dioksida total populasi pada tahun 2014 sebesar 9.88 ton dengan kesalahan penarikan contoh sebesar 26.67%. Nilai tersebut lebih rendah dibandingkan hasil pengukuran tahun 2013, yaitu 15.57 ton, yang diakibatkan oleh berbagai faktor.
Keyword: penarikan contoh sistematis berlapis, rehabilitasi hutan, serapan karbon

Judul: Pendugaan Cadangan Karbon Tanaman Rehabilitasi Hutan ConocoPhillips di Hutan Pendidikan Gunung Walat, Sukabumi, Jawa Barat.
Abstrak: Sejak tahun 2009 Hutan Pendidikan Gunung Walat (HPGW) melakukan kerjasama dengan ConocoPhillips Indonesia untuk meningkatkan cadangan karbon dengan melakukan kegiatan rehabilitasi hutan. Oleh karena itu, dilakukanlah penelitian ini yang bertujuan untuk mengetahui cadangan karbon pada blok rehabilitasi ConocoPhillips. Pendugaan cadangan karbon pada penelitian ini menggunakan metode stratified systemtic sampling with random start dengan intensitas sampling sebesar 16%, luas plot lingkaran 0,04 ha, dan plot contoh sebanyak 46 plot. Data yang digunakan pada penelitian ini adalah data diameter (dbh dan pangkal) dan tinggi total pohon. Dari data tersebut akan didapatkan nilai dugaan cadangan karbon serta nilai dugaan serapan karbon dioksida. Hasil pengukuran ini menunjukkan nilai dugaan cadangan karbon sebesar 19,83 ton, sehingga dapat menyerap karbon dioksida sebanyak 72,78 ton dengan kesalahan penarikan contoh sebesar 39,39%. Nilai dugaan cadangan karbon tahun 2016 mengalami peningkatan dari tahun sebelumnya yang bernilai sebesar 11,41 ton pada pengukuran tahun 2015 dan 2,69 ton pada pengukuran tahun 2014.
Keyword: serapan karbon dioksida, cadangan karbon, ConocoPhillips, rehabilitasi hutan

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