Judul: Penilaian Dampak Kebakaran pada Tegakan Akasia di BKPH Parung Panjang KPH Bogor, Perum Perhutani III Jawa Barat dan Banten
Abstrak: Forest fire is one of the problem in forest management. The objectives of the study was to measure the forest fire severity based on soil physical and chemical properties, and growth performance of the trees. The forest fire effects were assessed using fire severity method and forest health monitoring plot. The study indicated that the burned areas at BKPH Parung Panjang after two years included in low fire severity. The site properties and growth performance analysis showed that the fire has only affected on pH, Mg and tree diameter significantly, whereas the other parameters such as bulk density, P, N, Na, K, Ca and height were not significantly affected. In addition, both burned and unburned areas are classified as in health condition
Keyword: site properties, growth performance, forest health monitoring, fire severity

Judul: Valuation of Fire severity in Mount Lawu Forest, BKPH Lawu Selatan, KPH Lawu Ds, East Java
Abstrak: Selama beberapa tahun terakhir, hutan Gunung Lawu yang terletak di perbatasan antara Jawa Tengah dan Jawa Timur mengalami kejadian kebakaran hutan. termasuk kejadian pada tahun 2019 yang dikhawatirkan dapat merusak ekosistem di kawasan tersebut. Tujuan dari penelitian ini adalah untuk menilai tingkat keparahan kebakaran hutan Gunung Lawu menggunakan metode fire severity. Penelitian ini menggunakan karakteristik kondisi vegetasi dan kondisi tanah sebagai indikator penilaian. Plot yang dibangun di lokasi hutan terbakar dan tidak terbakar masing-masing berjumlah tiga jalur dengan setiap jalur terdiri dari 3 plot berukuran 20 m x 20 m. Hasil penelitian ini menunjukkan perbedaan pada kondisi vegetasi dan kondisi tanah di dua lokasi pengamatan. Perbedaan pada kondisi pohon meliputi perbedaan jumlah pohon hidup, lokasi kerusakan pada pohon, jenis kerusakan pada pohon, nilai indeks keanekaragaman jenis (H’), dan nilai kemerataan jenis (E). Perbedaan pada kondisi tanah meliputi nilai bulk density, pH, KTK, dan ketersediaan katioan basa (K, Na, Ca, Mg). Berdasarkan penilaian fire severity kebakaran hutan yang terjadi di hutan Gunung Lawu, BKPH Lawu Selatan, KPH Lawu Ds, Jawa Timur termasuk dalam kategori sedang, dengan total skor 58,3., Over the last few years, Gunung Lawu forest, which is located on the border between Central Java and East Java, has experienced forest fires, included in 2019, which could damage the ecosystem in the area. This research aims to assess the severity of Gunung Lawu forest fires using the fire severity method. This research uses the characteristics of vegetation conditions and soil conditions as indicators of assessment. The plots that were built in the burned and unburned forest consisted of three lanes each with each lane consisting of 3 plots 20 m x 20 m. The results of this study indicate tree and soil conditions differences in the two locations. The differences in vegetation condition include the difference in the number of living trees, the damage location, the types of damage, the diversity index value (H '), and the evenness value (E). Differences in soil conditions include bulk density, pH, CEC, and availability of alkaline ratio (K, Na, Ca, Mg). Based on the fire severity assessment of in Mount Lawu forest fire, BKPH Lawu Selatan, KPH Lawu Ds, East Java, it is classified in the medium category, with a total score 58,3.
Keyword: Fire Severity, Mount Lawu, Soil Condition, Vegetation Condition

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