Judul: Analysis of Factors Affecting People's Intention  to Buy Electric Cars in Jabodetabek
Abstrak: Penggunaan kendaraan bermotor di Indonesia selalu mengalami peningkatan dari tahun ke tahun. Ini menyebabkan pencemaran udara yang semakin tinggi. Penggunaan mobil listrik dinilai dapat mengurangi pencemaran udara. Namun, penggunaan mobil listrik di Indonesia masih mengalami hambatan. Penelitian ini bertujuan untuk menganalisis faktor yang menjadi pengaruh masyarakat untuk membeli mobil listrik di Jabodetabek melalui integrasi TAM dan TPB yang diperluas dengan menambahkan peubah Price Value, Perceived Risk, Environmental Awareness, dan Infrastructure Barrier. Responden pada penelitian ini sebanyak 200 responden. Teknik penarikan sampel dilakukan menggunakan non probability sampling dengan metode purposive sampling. Teknik analisis data yang digunakan adalah analisis deskriptif dan SEM PLS. Hasil dari penelitian ini menunjukkan perceived usefulness dan perceived ease of use memiliki pengaruh positif terhadap attitude. Peubah attitude, peceived behavioral control, dan price value memiliki pengaruh positif terhadap intention to buy electric car, sedangkan subjective norm, perceived risk, environmental awareness, dan infrastructure barier tidak berpengaruh signifikan terhadap intention to buy electric car., The use of motorized vehicles in Indonesia always increased from year to year. This caused higher air pollution. The use of electric cars was considered to reduce air pollution. However, the use of electric cars in Indonesia still experienced obstacles. This study aimed to analyze the factors that influenced people to buy electric cars in Jabodetabek through the integration of TAM and TPB, which were expanded by adding variables Price Value, Perceived Risk, Environmental Awareness, and Infrastructure Barrier. Respondents in this study were 200 respondents. The sampling technique was carried out using non-probability sampling with purposive sampling method. The data analysis technique used was descriptive analysis and SEM PLS. The results of this study indicated that perceived usefulness and perceived ease of use had a positive influence on attitude. The variables attitude, perceived behavioral control, and price value had a positive influence on the intention to buy electric cars, while subjective norm, perceived risk, environmental awareness, and infrastructure barriers had no significant effect on the intention to buy electric cars.
Keyword: electric car adoption, C-TAM-TPB, purchase intention, ground transportation, adopsi mobil listrik, niat pembelian, transportasi darat

Judul: The Effect of Environmental Concern and Government Policies on The Intention to Buy Electric Car: Analysis of Theory of Planned Behavior
Abstrak: Pasar mobil listrik di Indonesia masih tergolong rendah, padahal mobil listrik memiliki dampak positif terhadap lingkungan. Pemerintah Indonesia mendukung pertumbuhan dan perkembangan kendaraan listrik dengan mengeluarkan beberapa kebijakan untuk menarik niat beli masyarakat di Indonesia. Penelitian ini menganalisis kepedulian lingkungan dan kebijakan pemerintah yang mempengaruhi niat beli mobil listrik di Indonesia melalui perluasan theory of planned behavior dan memahami karakteristik responden serta merumuskan implikasi manajerial untuk meningkatkan niat beli mobil listrik di Indonesia. Pengumpulan data yang dibutuhkan dalam penelitian ini dilakukan menggunakan kuesioner online kepada responden. Kuesioner online dilakukan dengan cara mengirimkan link google form yang dibuat. Penelitian ini menggunakan teknik nonprobability sampling dengan kriteria responden yaitu masyarakat JABODETABEK yang bekerja mengunakan mobil di Jakarta yang telah mengetahui adanya mobil listrik di Indonesia. Convenience sampling dilakukan dengan tujuan untuk memudahkan dalam hal pengambilan data. Analisis dalam penelitian ini menggunakan Partial Least Square Structural Equation Modeling (PLS-SEM) dengan melibatkan 100 responden. Hasil yang diperoleh adalah masyarakat Indonesia setuju dengan adanya kepedulian terhadap lingkungan dan kebijakan pemerintah yang mendukung keberadaan mobil listrik di Indonesia dapat menumbuhkan niat beli masyarakat terhadap mobil listrik. Kepedulian lingkungan dan kebijakan pemerintah berpengaruh positif dan signifikan terhadap niat beli mobil listrik. Langkah utama dalam meningkatkan niat beli mobil listrik adalah dengan cara meningkatkan variabel norma subyektif, kesadaran lingkungan, sikap, kebijakan pemerintah dan kontrol perilaku.
Keyword: Environmental Concern, Government Policy, Theory of Planned Behavior, Purchased Intention, Electric Car

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