Judul: Tahapan Komunikasi Partisipatif dalam Proses Pengelolaan Wisata Underwater Desa Bangsring (Kecamatan Wongsorejo, Kabupaten Banyuwangi).
Abstrak: Komunikasi yang baik merupakan kunci keberhasilan pengelolaan Desa wisata. Peran aktif pengelola wisata, masyarakat lokal, dan pemerintah menjadi suatu kesatuan dalam proses pengelolaan wisata. Tujuan dari penelitian ini mengidentifikasi tahapan komunikasi partisipatif dalam proses pengelolaan desa wisata Bangsring Underwater. Metode yang digunakan dalam penelitian ini adalah metode sensus dengan menggunakan pendekatan kuantitatif didukung data kualitatif. Jumlah responden dalam penelitian ini adalah 40 responden. Mayoritas pengelola wisata Bangsring Underwater adalah laki-laki dan tergolong kedalam usia kategori dewasa. Terdapat empat indikator hubungan antara dukungan lingkungan dengan tahapan proses pengelolaan wisata Bangsring Underwater, yaitu dukungan masyarakat lokal berhubungan dengan tahap implementasi kegiatan, dukungan pemerintah dan mitra kerja berhubungan dengan tahap pemetaan isu, potensi, dan permasalahan, tahap merancang tindakan bersama, dan tahap monitoring dan evaluasi. Dukungan pemerintah dan mitra kerja tidak berupa pengalokasian dana melainkan dukungan secara fasilitas, pelatihan, dan promosi.
Keyword: desa wisata, karakteristik individu, karakteristik lingkungan, komunikasi partisipatif, pengelolaan wisata

Judul: Strategi Pengembangan Wisata Berbasis Masyarakat: Studi Kasus Kawasan Konservasi Bangsring Underwater
Abstrak: BUNDER (Bangsring Underwater) merupakan salah satu kawasan konservasi yang berada di Kabupaten Banyuwangi. Pada tahun 1970 masyarakat Bangsring menangkap ikan dengan menggunakan Potassium Sianida sehingga hasil tangkapan ikan semakin menurun. Hal tersebut mendasari adanya kesadaran masyarakat akan pentingnya melestarikan ekosistem laut. Pengelolaan Berbasis Masyarakat (PBM) merupakan pengelolaan wisata dimana masyarakat memiliki wewenang, tanggung jawab, dan pengambilan keputusan dalam pengelolaan sumberdaya. Berdasarkan pemaparan tersebut, maka dilakukan penelitian untuk mengetahui strategi pengembangan wisata berbasis masyarakat di pantai Bangsring, Kecamatan Wongsorejo, Banyuwangi, Jawa Timur. Metode yang digunakan dalam penelitian ini adalah metode sensus dengan jumlah responden sebesar 40 responden. Parameter ekonomi, ekologi, dan sosial meningkat akibat adanya PBM. Terdapat tujuh tahapan partisipasi masyarakat dalam proses pengelolaan wisata Bangsring Underwater yaitu integrasi; pemetaan isu, potensi, dan permasalahan; merancang tindakan bersama; implementasi; monitoring dan evaluasi; refleksi; umpan balik (feedback)., BUNDER (Bangsring Underwater) is one of the existing conservation areas in a Banyuwangi Regency. In 1970 the people of Bangsring caught fish using Potassium Cyanide, so the population of fish catches decreased. This underlies the existence of public awareness of preserving marine ecosystems. Community Based Management (CBM is management in which the community owns authority, responsibility, and decision-making in resource management. Based on this research, a study was conducted to determine community-based tourism development strategies at Bangsring Beach, Wongsorejo District, Banyuwangi, East Java. The method used in this study is the census method with a total of 40 respondents. Economic, ecological, and social parameters increase due to CBM. There are seven stages of community participation in the Bangsring Underwater tourism management process, which are integration; mapping of issues, potentials, and problems; planning joint actions; implementation; monitoring and evaluation; reflection; feedback.
Keyword: CBM, Community Participation, Tourism Development Strategy

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