Judul: Tingkat Konsumsi Kayu Bakar Masyarakat Desa Sekitar Hutan (Studi Kasus Desa Hegarmanah, Kecamatan Cicantayan, Kabupaten Sukabumi, Propinsi Jawa Barat).
Abstrak: Kayu bakar merupakan sumber energi yang telah lama digunakan untuk keperluan manusia. Produksi kayu bakar cenderung menurun seiring dengan berkurangnya areal penghasil kayu bakar seperti kebun dan hutan. Kebutuhan akan kayu bakar semakin meningkat khususnya didaerah pedesaan hal ini karena pertumbuhan penduduk, perkembangan industri dan adanya kelangkaan bahan bakar minyak. Untuk mengetahui penggunaan kayu bakar di pedesaan dan faktor-faktor yang mempengaruhi konsumsi kayu bakar maka penelitian ini perlu dilakukan
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Judul: Tingkat Konsumsi Kayu Bakar sebagai Sumber Energi Rumah Tangga di Desa Karacak, Kacamatan Leuwiliang, Kabupaten Bogor
Abstrak: Kayu bakar merupakan sumber energi yang mudah diperoleh tanpa menggunakan teknologi tinggi dan juga mudah pula dalam pemanfaatannya. Pemanfaatan kayu bakar memegang peranan yang sangat penting dalam pemenuhan kebutuhan sumber daya energi, terutama sebagai bahan bakar memasak pada sektor rumah tangga dengan menggunakan tungku. Masyarakat dalam pemenuhan kegiatan memasak saat ini lebih memilih bahan bakar komersial seperti LPG (Liquefied Petroleum Gas) bahkan energi listrik. Penelitian ini bertujuan untuk mengetahui tingkat konsumsi kayu bakar sebagai sumber energi rumah tangga berdasarkan tingkat kesejahteraan masyarakat serta mengetahui variabelvariabel yang berpengaruh terhadap tingkat konsumsi kayu bakar. Hasil penelitian menunjukan bahwa tingkat konsumsi kayu bakar terbesar di Desa Karacak yaitu pada kategori rumah tangga miskin sekali sebesar 3.01 m3/kapita/tahun dan hasil uji chi-square menunjukan bahwa variabel yang berpengaruh terhadap tingkat konsumsi kayu bakar yaitu jumlah anggota keluarga dan biaya pemakaian LPG.
Keyword: kayu bakar, kesejahteraan, pemanfaatan, tingkat konsumsi

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