Judul: Permintaan ekowisata wisatawan mancanegara di taman nasional Bromo Tengger Semeru Jawa Timur
Abstrak: Indonesian government through Ministry of Culture and Tourism has set year of 2008 as Indonesian visit year which target of international tourists visit amount of 7 million tourists. However, eventhough the target has set up, Indonesia still lack of data regarding tourism demand especially for ecotourism. Nowadays, ecotourism has become a trend and interesting for many tourists so can attract more international tourists to come. Bromo Tengger Semeru National Park (BTSNP) is one the most familiar Indonesian ecotourism destination. This research aims to get the illustration about international tourists demand at BTSNP. Research was conducted by interviewing internationals visitor. The election of respondents used purposive sampling technique. Collected data was descriptively analyzed. Some finding of this research are: international tourists visited BTSNP dominated by Dutch tourists (32%), man (61%), university graduated (69%), unmarried (63%), 25-31 years old (36%), employment (71%), using rent transportation (loo%), the activity was to see the crater of Bromo (100 tourists), duration of stayed was 1 day (60%), period of visitation was during vacation day (99%), group tour @I%), stayed on the hotel (91%), first visitation (95%), motivation was sightseeinglvacation (47%) and media as a source of information (54%).
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Judul: Nature-based tourism demand at semarang city for young age group
Abstrak: Semarang city is recently known as industry and business city. It also has potentials for tourism destination areas to young age group which known as having more leisure time compare to the other age group. The objectives of this research were to identity the potential demand and actual demand of nature-based tourism of young age group (15-24 years old) at Semarang City and the influencing factors. This research was in July to September 2010 at Semarang City. The respondents were highschool students, College students and nature-based tourists. Data were collected through literature review, interviews, questionnaires. Analysis of binary logistics regression was used to determine the factors which influence potential demand. Data of Statistic Center Agency (Badan Pusat Statistik-BPS, 2008) showed that the number of young age group individuals at Semarang City was 241.474 individuals. The study showed that the potential demand of nature – based tourism for young age group at Semarang City was 198.492 individuals (82,20% of the total number of individuals of young age group). The actual demand based on tourism objects was: 14.458 individuals (beach), 9.322 individuals (cave), 7.458 individuals (waterfall), and 20.144 individuals (mountain). Farther analysis used the binary logistics regression showed that reasons of visit (beautiful scenery, enjoy the scenery and fresh air) and length of visit were the factors which influence potential demand. Meanwhile, descriptive analysis showed that the factors which influence the actual demand were parents occupation, interest foward tourism objects, reason of visit, and time of visit.
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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