Judul: Potential and Hazard Management of Citumang Tourism Area, Pangandaran Regency
Abstrak: Potensi bahaya yang terdapat di kawasan wisata Citumang terdapat tiga jenis yaitu potensi bahaya fisik, biologi dan aktivitas manusia. Pengambilan data potensi bahaya ini dilakukan pada bulan Agustus tahun 2020. Penelitian ini dilakukan dengan menggunakan jenis data primer dan sekunder. Analisis potensi bahaya di kawasan wisata Citumang dianalisis menggunakan penilaian risiko menurut UNEP 2008 untuk bahaya fisik dan biologi dan NPSA 2008 untuk penilaian bahaya aktivitas manusia. Potensi bahaya fisik yang terdapat di Citumang memiliki tingkat risiko sedang dan rendah. Potensi bahaya biologi di Citumang mempunyai nilai risiko rendah dan potensi bahaya aktivitas manusia mempunyai nilai yang rendah. Hasil penilaian risiko dari setiap aspek ini ditangani dengan pilihan manajemen pengurangan risiko karena manajemen risiko ini dibuat untuk mengevaluasi setiap risiko yang terjadi di kawasan wisata Citumang., There are three types of potential hazards in the Citumang tourism area, the potential is a physical, biological and human activity. This research was conducted in August 2020 using a primary dan secondary data type. Data analysis of potential hazards in the Citumang tourism area use a risk assessment according to UNEP 2008 for physical and biological hazards and NPSA 2008 for hazard assessment of human activities. The potential physical hazards contained in Citumang have a low medium level of risk. Potential biological hazards in Citumang have a low risk and the potential hazards of human activities have a low value. The result of risk assessment from each aspect are handled with risk reduction management option because risk management is designed to evaluate every risk that occursin the Citumang tourism area.
Keyword: Kawasan wisata Citumang, manajemen bahaya, potensi bahaya, Citumang tourism area, risk management, hazard potential

Judul: Potensi Bahaya di Kawasan Wisata Alam Aek Nabara, Sumatra Utara
Abstrak: Desa Aek Nabara secara geografis berada di lembah sempit yang diapit oleh dua Gunung, yakni Gunung Sibual - buali dan Gunung Lubuk Raya yang berada di ketinggian sekitar 800 mdpl. Potensi bahaya dapat mengancam keselamatan pengunjung, yang merupakan aspek penting dalam kegiatan wisata. Kondisi tempat wisata dapat mempengaruhi jumlah kunjungan wisata. Potensi bahaya di kawasan wisata alam Aek Nabara yang diinventarisasi adalah bahaya fisik, biologi, dan aktivitas manusia. Inventarisasi dan analisis potensi bahaya dilakukan menggunakan panduan yang dibuat oleh United Nation Environment Programme (UNEP), metode Job Safety Analysis (JSA), dan Peraturan Menteri Kesehatan Republik Indonesia Nomor 32 Tahun 2017. Potensi bahaya fisik yang ada di kawasan wisata alam Aek Nabara memiliki nilai risiko rendah, sedang dan tinggi. Banyak satwa sering terlihat di kawasan wisata alam Aek Nabara, seperti owa, monyet ekor panjang, lutung, burung rangkong, dan yang kadang dapat dijumpai seperti orang utan dan harimau. Akses yang jarang dilewati angkutan umum dan masih jarang diketahui masyarakat luar, membuat pengunjung di kawasan wisata alam Aek Nabara masih sangat sedikit. Manajemen pengurangan risiko bahaya kawasan wisata alam Aek Nabara dilakukan dengan mengevaluasi setiap risiko bahaya yang terdapat pada kawasan, kemudian membuat rekomendasi pilihan manajemen yang harus dilakukan.
Keyword: Aek Nabara, Gunung Lubuk Raya, Gunung Lubuk Sibual - buali, manajemen risiko, potensi bahaya

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