Judul: Analisis Titik Panas (Hotspot) dan Curah Hujan di Kabupaten Mappi, Provinsi Papua Selatan
Abstrak: Kabupaten Mappi merupakan salah satu wilayah di Provinsi Papua Selatan yang memiliki jumlah hotspot tertinggi setelah Merauke dalam satu dekade terakhir. Penelitian bertujuan menganalisis pola sebaran hotspot dan keterkaitannya dengan curah hujan pada periode 2012-2021 di Kabupaten Mappi, Provinsi Papua Selatan. Sumber yang digunakan dalam penelitian adalah data hotspot dari citra satelit MODIS Terra/Aqua dan data curah hujan dari NASA LaRC Power yang dianalisis menggunakan analisis deskriptif dan analisis regresi. Hasil penelitian menunjukkan adanya fluktuatif jumlah hotspot pada rentang tahun 2012-2021 dan puncak hotspot terjadi pada tahun 2015. Jumlah hotspot pada rentang tahun tersebut adalah 3879 titik. Sebanyak 1415 titik (36,48%) tersebar pada lahan gambut dan 2464 titik (63,52%) pada lahan mineral. Hasil analisis regresi menunjukkan bahwa hubungan antara hotspot dengan curah hujan memiliki nilai p-value 0,006, artinya p-value < 0,05 menunjukkan korelasi keduanya berpengaruh secara signifikan.
Keyword: forest and land firest, hotspot, Mappi District, rainfall

Judul: Hotspot and Rainfall Analysis Period in Mappi District, South Papua Province
Abstrak: Kabupaten Mappi merupakan salah satu wilayah di Provinsi Papua Selatan yang memiliki jumlah hotspot tertinggi setelah Merauke dalam satu dekade terakhir. Penelitian bertujuan menganalisis pola sebaran hotspot dan keterkaitannya dengan curah hujan pada periode 2012-2021 di Kabupaten Mappi, Provinsi Papua Selatan. Sumber yang digunakan dalam penelitian adalah data hotspot dari citra satelit MODIS Terra/Aqua dan data curah hujan dari NASA LaRC Power yang dianalisis menggunakan analisis deskriptif dan analisis regresi. Hasil penelitian menunjukkan adanya fluktuatif jumlah hotspot pada rentang tahun 2012-2021 dan puncak hotspot terjadi pada tahun 2015. Jumlah hotspot pada rentang tahun tersebut adalah 3879 titik. Sebanyak 1415 titik (36,48%) tersebar pada lahan gambut dan 2464 titik (63,52%) pada lahan mineral. Hasil analisis regresi menunjukkan bahwa hubungan antara hotspot dengan curah hujan memiliki nilai p-value 0,006, artinya p-value < 0,05 menunjukkan korelasi keduanya berpengaruh secara signifikan., Mappi Regency is one of the areas in South Papua Province which has the highest number of hotspots after Merauke in the last decade. The research aims to analyze the pattern of hotspot distribution and its relationship to rainfall in the 2012-2021 period in Mappi District, South Papua Province. The sources used in this study were hotspot data from the MODIS Terra/Aqua satellite imagery and rainfall data from NASA LaRC Power which were analyzed using descriptive analysis and regression analysis. The results showed that there was a fluctuation in the number of hotspots in the 2012-2021 range and the peak of hotspots occurred in 2015. The number of hotspots in that year range was 3879 points. A total of 1415 points (36,48%) are spread on peat land and 2464 points (63,52%) on mineral land. The results of the regression analysis show that the relationship between hotspots and rainfall has a p-value of 0,006, meaning that the p-value is < 0,05 which indicates that the correlation between the two has a significant effect.
Keyword: forest and land fires, hotspot, Mappi District, rainfall

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