Judul: The Impact of Forest and Peatland Fires on Humans and The Environment (Case Study : Village Bunsur, Sungai Apit District, Siak Regency, Riau Province)
Abstrak: Penelitian ini menggunakan perspektif ekologi manusia untuk menghubungkan dampak kebakaran hutan dan lahan gambut terhadap kondisi manusia dan lingkungan hidup di Desa Bunsur, Kecamatan Sungai apit, Kabupaten Siak, Provinsi Riau. Responden penelitian ini merupakan rumah tangga petani pemilik lahan yang pernah mengalami kebakaran pada lahannya. Kejadian kebakaran yang dialami terhitung sejak tahun 2014-2019 dengan jumlah responden 40 rumah tangga petani yang dipilih berdasarkan teknik bola salju. Pendekatan yang dilakukan menggunakan pendekatan kuantitatif yang didukung oleh data kualitatif. Hasil penelitian ini menunjukkan, pertama, secara keseluruhan penyebab terjadinya kebakaran berasal dari tingkah laku manusia, yang kemudian diperparah dengan kondisi alam pada lahan sehingga kebakaran menjadi lebih parah. Kedua, secara keseluruhan tingkat keparahan kebakaran hutan dan lahan gambut ditentukan oleh kondisi lahan gambut yang sangat kering dan vegetasi lahan belukar ketika peristiwa kebakaran berlangsung. Ketiga, penelitian ini menunjukkan bahwa terdapat hubungan nyata positif antara faktor alam dengan durasi kebakaran, hubungan nyata positif antara faktor alam dengan tinggi api saat kebakaran berlangsung, hubungan nyata positif antara tingkat keparahan kebakaran hutan dan lahan gambut dengan dampak yang ditimbulkan pada masyarakat di Desa Bunsur., This study uses a human ecology perspective to relate the impact of forest and peatland fires on human conditions and environment in Bunsur Village, Sungai Apit District, Siak Regency, Riau Province. Respondents of this study were farmer households who owned land that had experienced fires on their land. The incidence of fire experienced since 2014-2019 with a total of 40 farmer households selected based on the snowball technique. The approach used is a quantitative approach that is supported by qualitative data. The results of this study indicate, first, that the overall cause of the fires tends to come from human behavior, which is then exacerbated by natural conditions on the land so that the fires become more severe. Second, the overall severity of forest and peatland fires is determined by the condition of very dry peatland shrubby vegetation when the first occur. Third, this study shows that there is a significant positive relationship between natural factors and the duration of fire, a significant positive relationship between natural factors and the height of the fire during the fire, a significant positive relationship between the severity of forest and peatland fires and the impact on the community in Bunsur Village.
Keyword: Impact of peatland fires, factors causing of fire, fire severity

Judul: Community Behavior and Perceptions of Peat Fires in Tangkit Baru Village Jambi Province
Abstrak: Kabupaten Muaro Jambi yang memiliki sebaran gambut seluas 229.703.90 ha kerap kali mengalami kebakaran hutan dan lahan khususnya di Desa Tangkit Baru Kecamatan Sungai Gelam yang sebagian besar daerahnya merupakan lahan gambut. Penelitian bertujuan menganalisis perilaku masyarakat yang dapat memicu terjadinya kebakaran gambut dan menganalisis persepsi dan tingkat pengetahuan masyarakat terhadap pengendalian kebakaran gambut di Desa Tangkit Baru. Analisis data penelitian dilakukan secara deskriptif melalui wawancara menggunakan kuisioner yang berisi 20 pernyataan positif mengenai pengelolaan lahan gambut yang berkelanjutan, dampak dari kebakaran gambut, serta langkah pengendalian kebakaran gambut dari partisipasi masyarakat menggunakan skala likert. Hasil analisis perilaku masyarakat yang dapat memicu terjadinya kebakaran gambut pada lokasi penelitian di lahan gambut merupakan kegiatan sonor, pembersihan lahan dengan pembakaran, dan membakar sampah. Persepsi dan tingkat pengetahuan masyarakat terhadap pengendalian kebakaran gambut termasuk dalam kategori tinggi dan memiliki korelasi hubungan yang sangat kuat. Hubungan antara pengetahuan dan persepsi masyarakat di Desa Tangkit Baru memiliki korelasi positif., Muaro Jambi Regency, which has a peat distribution area of 229,703.90 ha, often experiences forest and land fires, especially in Tangkit Baru Village, Sungai Gelam District, where most of the area is peatland. The research aims to analyze community behavior that can trigger peat fires and analyze community perceptions and level of knowledge regarding peat fire control in Tangkit Baru Village. Research data analysis was carried out descriptively through interviews using a questionnaire containing 20 positive statements regarding sustainable peatland management, the impact of peat fires, as well as steps to control peat fires from community participation using a Likert scale. The results of the analysis of community behavior that can trigger peat fires at research locations on peatlands are sonor activities, land clearing by burning, and burning rubbish. The community's perception and level of knowledge regarding peat fire control is in the high category and has a very strong correlation. The relationship between knowledge and community perception in Tangkit Baru Village has a positive correlation.
Keyword: Kebakaran gambut, Muaro Jambi, Perilaku masyarakat, Persepsi masyarakat, Tangkit Baru

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