Judul: Hubungan Keterdedahan Media Sosial mengenai Protokol Kesehatan Covid-19 dan Perilaku New Normal Masyarakat Kota Depok
Abstrak: Pandemi Covid-19 membuat masyarakat Indonesia harus menerapkan perilaku new normal dalam aktivitas sehari-hari dengan protokol kesehatan Covid-19 “3M: Memakai masker, Mencuci tangan, dan Menjaga jarak” yang disebarluaskan melalui berbagai media sosial. Tujuan penelitian untuk mendeskripsikan tingkat keterdedahan media sosial dan keterdedahan selektif media sosial mengenai Protokol Kesehatan Covid-19, Mendeskripsikan perilaku new normal pada masyarakat Kota Depok, menganalisis hubungan karakteristik pengguna media sosial dan tingkat keterdedahan media sosial mengenai protokol kesehatan Covid-19, dan menganalisis hubungan keterdedahan media sosial mengenai protokol kesehatan Covid-19 dan perilaku new normal masyarakat Kota Depok. Penelitian bersifat explanatory research, dengan pendekatan kuantitatif menggunakan instrumen dan pendekatan kualitatif melalui wawancara mendalam. Hasil penelitian menunjukkan 1) tingkat keterdedahan masyarakat terhadap media sosial mengenai protokol kesehatan Covid-19 berada pada kategori tinggi dengan Instagram yang paling banyak diakses; 2) penerapan new normal aspek kognitif dan afektif tinggi, namun rendah pada aspek konatif; 3) karakteristik pengguna media sosial seperti usia dan tingkat pendidikan memiliki hubungan yang nyata terhadap tingkat keterdedahan media sosial; 4) tingkat keterdedahan media sosial memiliki hubungan sangat nyata dengan tingkat penerapan perilaku new normal.
Keyword: communication channels, health behavior, media effects, selective exposure

Judul: Effectiveness of Cyber Government Public Relations in Dissemination of Health Information as a Form of Crisis Communication (Case: Covid-19 Health Information Bogor Regency Community)
Abstrak: Kabupaten Bogor dilanda krisis pandemi Covid-19. Berbagai upaya telah dilakukan pemerintah salah satunya dengan diseminasi informasi kesehatan oleh Gugus Tugas Percepatan Penanganan Covid-19 Kabupaten Bogor. Diseminasi secara online utamanya dilakukan pada website, Instagram, Twitter, dan Facebook. Namun, angka penularan Covid-19 dan pelanggaran protokol masih terus meningkat. Maka dari itu, tujuan dari penelitian ini adalah untuk melihat sejauh mana efektivitas strategi cyber GPR Gugus Tugas Percepatan Penanganan Covid-19 dalam diseminasi informasi kesehatan sebagai bentuk komunikasi krisis. Metode yang digunakan adalah metode penelitian survei online dengan menggunakan pendekatan kuantitatif yang didukung dengan kualitatif. Data kuantitatif diperoleh dengan menggunakan kuesioner online dan data kualitatif dilakukan dengan wawancara mendalam baik secara online maupun tatap muka. Pengambilan responden dilakukan dengan mengombinasikan teknik sampling voluntary dan purposive. Hasil penelitian menunjukkan bahwa terdapat hubungan antara usia dan tingkat pendidikan dengan tingkat diseminasi. Hanya pada website penilaian terhadap media berhubungan dengan tingkat keterdedahan responden. Sedangkan, tidak ditemukan hubungan antara sikap dengan tingkat keterdedahan responden
Keyword: cyber government public relations, komunikasi kesehatan, komunikasi krisis

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