Judul: Identification of Gas Hydrate Zones on Bottom Simulating Reflector of 2D Seismic Sections in North Bali Waters
Abstrak: Seismik refleksi merupakan salah satu metode akustik bawah air yang digunakan untuk mendeteksi sumberdaya mineral dan gas. Salah satu gas yang dapat ditemukan dan menjadi objek penelitian ini adalah gas hidrat. Gas hidrat merupakan salah satu sumberdaya alternatif non-konvensional yang dapat menjadi pengganti dari sumberdaya minyak dan gas konvensional. Gas hidrat dapat diidentifikasi dengan memeriksa keberadaan Bottom Simulating Reflector pada pemrosesan data seismik 2D. Tujuan penelitian ini adalah memberikan informasi mengenai keberadaan Bottom Simulating Reflector di penampang seismik 2D serta mengidentifikasi zona gas hidrat pada Perairan Bali Utara pada penampang seismik 2D. Ditemukan keberadaan Bottom Simulating Reflector pada CDP 35- 812 dengan kedalaman ttwt 1526-1582 ms, dengan karakteristik high amplitudereverse polarity jika dibandingkan dengan reflector dasar laut. Data yang digunakan merupakan hasil akuisisi Kementerian ESDM tahun 2017 di Perairan Utara Bali.
Keyword: Bottom Simulating Reflector, gas hydrate, North Bali Waters, seismic reflection.

Judul: Deteksi Gas Hidrat Berdasarkan Perubahan Karakter Seismik di Perairan Laut Aru Menggunakan Teknologi Low-Frequency Acoustic.
Abstrak: Gas hidrat merupakan salah satu jenis hidrokarbon yang berbentuk padat dan terbentuk pada sedimen dasar laut. Gas hidrat tercipta pada suhu dan tekanan tinggi, yang tersusun dari molekul air dan gas. Gas hidrat berpotensi sebagai alternatif untuk menggantikan minyak dan gas bumi. Keberadaan gas hidrat di dasar laut dapat dideteksi dengan teknologi low-frequency acoustic seismic. Penelitian ini dilakukan dengan tujuan untuk melakukan deteksi keberadaan gas hidrat di Perairan Laut Aru berdasarkan perubahan karakter seismik gas hidrat. Metode deteksi keberadaan gas hidrat dilakukan dengan melihat kenampakan Bottom Simulating Reflectors (BSR) pada penampang seismik. Keberadaan gas hidrat di dasar laut dicirikan dengan memotong stratigrafi, membalikan polaritas, amplitudo tinggi, dan bentuknya mengikuti dasar laut. Data yang digunakan merupakan hasil akuisisi Pusat Penelitian dan Pengembangan Geologi Laut (PPPGL) tahun 2016 di Perairan Laut Aru.
Keyword: bottom simulating reflectors, gas hidrat, low-frequency, seismik

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