Judul: The Influence of Attitudes, Subjective Norms, Behavior Control, and Health Awareness on Intention to Consume Jamu during the Covid-19 Pandemic
Abstrak: Jamu merupakan obat tradisional berbahan alami yang sudah dikonsumsi masyarakat Indonesia untuk mendapatkan manfaat kesehatan seperti pencegahan dan pengobatan penyakit, menjaga kebugaran dan meningkatkan stamina tubuh. Pada masa pandemic Covid-19, konsumsi jamu berbahan dasar empon-empon seperti temulawak, jahe, kunyit, dan sereh banyak direkomendasikan untuk dikonsumsi. Penelitian ini bertujuan untuk menganalisis pengaruh sikap, norma subjektif, kontrol perilaku dan kesadaran kesehatan terhadap niat konsumsi jamu pada masa pandemic Covid-19. Penelitian ini menggunakan data primer dari 226 responden di Jakarta melalui penyebaran kuesioner secara daring. Penelitian ini menggunakan metode analisis deskriptif dan Structural Equility Modeling-Partial Least Square (SEM-PLS). Hasil penilitian menunjukan bahwa variabel sikap, norma subjektif, kontrol perilaku dan kesadaran kesehatan memiliki pengaruh positif dan signifikan terhadap niat masyarakat Jakarta mengonsumsi jamu di masa pandemic Covid-19., Jamu is a traditional medicine made from natural ingredients that have been consumed by the Indonesian people to get health benefits such as prevention and treatment of diseases, maintaining fitness and increasing stamina. During the Covid-19 pandemic, consumption of herbs made from empon-empon such as ginger, ginger, turmeric, and lemongrass were recommended. This study aims to analyze the influence of attitudes, subjective norms, behavioral control and health awareness on the intention to consume herbal medicine during the Covid-19 pandemic. This study used primary data from 226 respondents in Jakarta through online questionnaires. This study used descriptive analysis methods and Structural Equility Modeling-Partial Least Square (SEM-PLS). The results showed that the variables of attitude, subjective norms, behavioral control and health awareness had a positive and significant effect on the intention of the people of Jakarta to consume herbal medicine during the Covid-19 pandemic.
Keyword: Covid-19, herbal medicine, health awareness, SEM-PLS, theory of planned behavior

Judul: The Influence of Consumer Perception, Preference, Affective Attitude, Knowledge, and Experience on The Purchase Intention of Research-Based Herbal Medicines
Abstrak: Industri herbal dan jamu diperkirakan mengalami pertumbuhan yang pesat baik di pasar domestik maupun global. Akan tetapi masih banyak kendala yang dihadapi oleh pengguna obat herbal karena masih adanya obat-obat herbal yang mengandung Bahan Kimia Obat (BKO) dan klaim berlebih, selain itu penggunaan obat di masyarakat cenderung didominasi oleh obat kimia dibandingkan dengan obat herbal. Penelitian ini bertujuan untuk menganalisis pengaruh persepsi, preferensi, sikap afektif, pengetahuan dan pengalaman terhadap niat membeli produk obat herbal berbasis riset di Kota Tangerang. Penentuan sampel dalam penelitian menggunakan probability sampling. Metode analisis yang digunakan yaitu analisis deskriptif dan PLS-SEM. Hasil penelitian menunjukkan bahwa preferensi dan sikap afektif meningkatkan niat beli produk obat herbal berbasis riset. Sedangkan persepsi, pengetahuan dan pengalaman tidak meningkatkan niat beli produk obat herbal berbasis riset. Penelitian ini menyarankan agar perusahaan meningkatkan preferensi dan sikap afektif konsumen dengan menjalin komunikasi dengan konsumen melalui konten promosi atau iklan dan mempertahankan atribut-atribut pada produk., The Influence of Consumer Perception, Preference, Affective Attitude, Knowledge, and Experience on The Purchase Intention of Research-Based Herbal Medicines. Supervised by ETRIYA The herbal medicine industry is expected to grow in both the domestic and global markets. However, there are still many obstacles faced by herbal drug users because there are still herbal medicines containing medicinal chemicals (MC) and excessive claims, besides that the use of drugs in society tends to be dominated by chemical drugs compared to herbal medicines. This study aims to analyze the influence of perceptions, preferences, affective attitudes, knowledge and experience on the intention to buy research-based herbal medicines in Tangerang City. Determination of the sample in the study using probability sampling method. The analytical method used is descriptive analysis and PLS-SEM. The results of the study show that preferences and affective attitudes increase the purchase intention of research-based herbal medicines. Meanwhile, perception, knowledge and experience did not increase the intention to buy research-based herbal medicines. This research suggests that companies increase consumer preferences and affective attitudes by establishing communication with consumers through promotional or advertising content and maintaining product attributes.
Keyword: Affective attitude, Perception, Preference, Purchase intention, Herbal medicine

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