Judul: Kajian Potensi Transmisi Penyakit Demam Berdarah Dengue Berdasarkan Curah Hujan dan Suhu di Jawa Tengah
Abstrak: Dengue hemorrhagic fever (DHF) is a viral disease which has spread throughout Indonesia over the past 25 years. Ae. aegypti is the main vector of the disease. In Indonesia, especially in Central Java, there has been an upward trend in the incidence of dengue hemorrhagic fever. Therefore some efforts to suppress an outbreak of this disease had been done by the government with focus against the vector. This research aims to determine and mapping the transmission potential (TP) of DHF in Central Java under 4 principal seasons: rainy (December- February), transition 1 (March – May), dry (June-August) and transition 2 (September – November) at 3 rainfall conditions ( below normal, normal and above normal years) using vectorial capacity (VC) method. The results show that the maximum average VC for under normal years occur on December-February, whereas for normal and above normal years its occurs on March-May. In every rainfall condition, the minimum VC occur on June-August when rainfall is minimum. Based on resulted map from this research, in coastal area of northern and southern site of Central Java which is lowland area, TP were higher than in central area which is highland. TP on city with high population such as Tegal, Semarang, and Surakarta were higher. Nevertheless, between VC and incidence rate (IR) were significant with coefficient correlation 0.057, caused by there weren’t interventions between 35 districts in Central Java to supress the number of DHF disease in case of sanitation, vector controls (fogging, aerial spraying, making abate), immunity of society, etc.
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Judul: Appropriateness of the Onset Period of Dengue Fever with the Onset of Rainy Season and Determining the Level of Case Vulnerability in Central Java
Abstrak: Demam Dengue (DD) merupakan penyakit yang sering terjadi di Indonesia. Salah satu faktor iklim yang berpengaruh terhadap penyakit DD adalah curah hujan. Setiap daerah memiliki tingkat kerawanan kasus yang berbeda-beda, sehingga perlu penentuan tingkat kerawanan untuk menentukan prioritas penanggulangannya. Penelitian ini bertujuan (a) mengetahui kesesuaian periode onset kejadian DD dengan periode onset musim hujan (MH), serta (b) mengetahui tingkat kerawanan kasus DD di Provinsi Jawa Tengah. Periode onset MH ditentukan berdasarkan anomali kumulatif dan kriteria berjenjang BMKG. Periode onset kejadian DD juga ditentukan berdasarkan anomali kumulatif dimana nilai minimum diidentifikasi sebagai periode onset. Tingkat kerawanan ditentukan berdasarkan tingkat peluang dari nilai indeks kerawanan. Hasil menunjukkan bahwa penentuan periode onset MH berdasarkan metode kriteria berjenjang BMKG memberikan persentase kesesuaian lebih tinggi dengan onset kejadian DD yaitu sebesar 62% dibandingkan dengan metode anomali kumulatif dengan persentase sebesar 53%. Periode onset kejadian DD yang terjadi bersamaan dengan onset MH kebanyakan terjadi di bulan Desember. Tingkat kerawanan kasus DD berada pada kategori agak aman (2 kabupaten), agak rawan (1 kabupaten), rawan (3 kabupaten), sangat rawan (23 kabupaten/kota), hingga amat sangat rawan (6 kabupaten/kota)., Dengue Fever (DF) is a disease that often occurs in Indonesia. One of the climatic factors that affect DF disease is rainfall. Each region has a different level of case vulnerability, so it is necessary to determine the level of vulnerability to choose the priority of countermeasures. This research aims to (a) determine appropriateness of the onset period of dengue fever with the onset of rainy season (RS), and (b) determine the level of vulnerability for DF cases in Central Java Province. The onset period of RS is determined based on the cumulative anomalies and tiered criteria of BMKG. The onset period of DF events is also determined based on cumulative anomalies, which is the minimum value is identified as the onset period. The level of vulnerability is determined based on the probability level of vulnerability index. The results show that determining the onset period of RS based on tiered criteria of BMKG provides a higher percentage of appropriateness with the onset of DF events, namely 62% compared to the cumulative anomalies method with a percentage of 53%. The onset period of DF events which occurred simultaneously with the onset of RS mostly occurred in December. The level of vulnerability for DF cases is in the category of slightly safe (2 districts), slightly vulnerable (1 district), vulnerable (3 districts), very vulnerable (23 districts/cities), and extremely vulnerable (6 districts/cities).
Keyword: curah hujan, Faktor Meteorologi, demam dengue, kerawanan, periode onset

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