Judul: Analisis Kelekatan Teman Sebaya dan Kemandirian pada Remaja Perdesaan serta Kaitannya dengan Temperamen Remaja
Abstrak: Penelitian ini bertujuan untuk menganalisis hubungan antara kelekatan teman sebaya dan kemandirian pada remaja perdesaan serta kaitannya dengan temperamen remaja. Desain penelitian menggunakan cross sectional study. Penelitian dilaksanakan di Kecamatan Ciampea, Kabupaten Bogor. Contoh dalam penelitian ini adalah remaja yang diasuh langsung oleh ibunya, dari tiga SMP terpilih di lokasi penelitian. Jumlah contoh dalam penelitian adalah 100 remaja yang terpilih melalui cluster random sampling. Hasil menunjukkan bahwa semakin dominan temperamen dalam aspek kemampuan mengontrol emosi (effortful control) dan temperamen dalam aspek keinginan akan kehangatan serta kedekatan (affiliativeness) maka semakin lekat remaja dengan teman sebayanya. Selanjutnya, semakin meningkat temperamen dalam aspek mengontrol emosi (effortful control) dan kelekatan teman sebaya maka semakin meningkat kemandirian remaja. Hasil lainnya menunjukkan semakin dominan temperamen remaja terhadap mudahnya mengalami stress (negative affect) maka semakin menurun kemandirian remaja. Hasil uji regresi menunjukkan bahwa penurunan skor temperamen negative affect dan peningkatan skor kelakatan teman sebaya secara konsisten berpengaruh terhadap peningkatan skor kemandirian remaja perdesaan.
Keyword: kelekatan teman sebaya, kemandirian, remaja, temperamen

Judul: Pengaruh Metode Sosialisasi dan Kelekatan Teman Sebaya terhadap Kekuatan Karakter Anak Usia Sekolah pada Keluarga Perdesaan
Abstrak: Penelitian ini bertujuan untuk menganalisis pengaruh metode sosialisasi dan kelekatan teman sebaya terhadap kekuatan karakter anak usia sekolah pada keluarga perdesaan. Penelitian ini menggunakan desain cross sectional study. Pengumpulan datanya dengan teknik wawancara dan menggunakan kuesioner terstruktur. Kerangka contoh penelitian adalah keluarga lengkap yang memiliki anak kelas 4 dan 5 yang bersekolah di dua SD Negeri di Kecamatan Pamijahan, Kabupaten Bogor. Sebanyak 100 keluarga dengan responden ibu dan anak dipilih secara acak proporsional. Hasil menunjukkan bahwa metode sosialisasi sosiokultur dan pendampingan mempunyai rata-rata tertinggi dibandingkan metode sosialisasi lain. Rata-rata tertinggi pada kelekatan teman sebaya ditemukan pada dimensi kepercayaan. Hasil model regresi menunjukkan bahwa hanya usia dan variabel kelekatan dengan teman sebaya yang berpengaruh nyata terhadap kekuatan karakter anak usia sekolah pada keluarga perdesaan.
Keyword: Character Strength, Peer Attachment, School-age Children, Socialization Methods, Rural Families, Human ecology, Cross sectional study, Family school partnership

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