Judul: Kejadian Penyakit Infeksi Saluran Pernapasan Akut (ISPA) di Provinsi Kalimantan Timur oleh Pengaruh Jumlah Titik Panas (Hotspot) dan Curah Hujan
Abstrak: Forest fires can be related to the disease of ARI/ISPA. ARI is a respiratory disease caused by air pollution and bacterial infections. This study aimed to measure the strength forest fire (hotspot) and rainfall to the incidence of Acute Respiratory Infection (ARI) disease in the province of East Kalimantan. The method used is the analysis of the relationships between hotspot and rainfall variables with ARI. The disease found easier in the condition with or without forest fire. When the hotspot is less than 58 points influence on ARI are not clearly noticed. However, if the points of hotspots is more than 58, influence hotspot more clearly noticed, ie the rise hotspot increases the disease of ARI. In general, more hotspots occurred while negative of rainfall anomalies in the months around August to October, also the months the strong influence, on increasing hotspot ARI 80% for ARI Pneumonia and 52% for ARI Non Pneumonia.
Keyword: 

Judul: The Influence of Meteorological Factors and Particulate on Accute Respiratory Infection (ARI) in Jambi in Forest Fire Periods
Abstrak: Kebakaran hutan dan lahan (karhutla) seringkali terjadi di beberapa wilayah di Pulau Sumatera, contohnya Provinsi Jambi. Kota Jambi merupakan salah satu kota yang terdampak. Dampak yang ditimbulkan berupak kabut asap sehingga menyebabkan terjadinya peningkatan ISPUPM10 di Kota Jambi. Fenomena tersebut menjadi salah satu faktor meningkatnya penderita Infeksi Saluran Pernapasan Akut (ISPA) di Kota Jambi. Penelitian ini dilakukan untuk mengetahui pengaruh karhutla dan faktor meteorologi terhadap kejadian ISPA di Kota Jambi tahun 2015 hingga2019. Metode yang digunakan adalah analisis sebaran jumlah hotspot dan arah angin menggunakan windrose serta analisis regresi linear berganda. Hasil menunjukan pada bulan September 2015 dan 2019 (jumlah hotspot terbanyak) angin bergerak dari arah tenggara ke barat laut (Kab. Muaro Jambi ke Kota Jambi).Berdasarkan analisis jumlah hotspot dengan ISPU PM10 didapatkan bahwa tahun 2015 dan 2019 kualitas udara di Kota Jambi dipengaruhi oleh karhutla, sedangkan pada tahun 2016, 2017, dan 2018 karhutla tidak memengaruhi kualitas udara. Tahun 2015 merupakan tahun penderita ISPA dipengaruhi oleh tingginya partikulat. Penderita ISPA disebabkan oleh pengaruh linear penurunan kualitas udara dan rendahnya curah hujan. Tahun 2016 merupakan tahun penderita ISPA dipengaruhi oleh faktor meteorologi. Tingginya curah hujan memicu rendahnya resistensi tubuh terhadap lingkungan. Tahun 2019 merupakan tahun penderita ISPA dipengaruhi oleh tingginya partikulat serta faktor meteorologi secara tidak linear.
Keyword: ARI, Forest fires, Jambi City, Jambi Province, PM10

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