Judul: Estimasi Dampak Income Shock terhadap Pola Konsumsi Pangan Rumah Tangga di Provinsi DKI Jakarta
Abstrak: Kejadian bencana alam, pandemi penyakit seperti Covid-19, krisis sosialekonomi dan politik dapat menimbulkan berbagai dampak negatif terhadap ketersediaan, distribusi, harga pangan, pendapatan rumah tangga (income shock), dan konsumsi pangan secara kuantitas dan kualitas. Penelitian ini bertujuan untuk mengestimasi perubahan konsumsi pangan rumah tangga di Provinsi DKI Jakarta melalui simulasi akibat terjadinya income shock. Data yang digunakan dalam penelitian ini merupakan data sekunder Susenas 2017, data pengeluaran konsumsi, serta data pemberian bantuan sosial dari pemerintah provinsi. Konsumsi energi dan protein serta skor PPH di Provinsi DKI Jakarta semakin tinggi seiring dengan peningkatan pendapatan. Kejadian income shock menyebabkan terjadinya penurunan konsumsi pada seluruh kelas pendapatan. Pada rumah tangga dengan kelas pendapatan terendah, tingkat kecukupan energi dan protein menurun sekitar 5% hingga 20%. Penurunan tingkat kecukupan juga dialami pada kelompok pendapatan lain namun masih dalam kategori cukup. Pemberian bantuan tunai bila seluruhnya digunakan untuk pangan membantu meningkatkan konsumsi energi, protein, serta pangan strategis rumah tangga, namun pemberian bantuan non-tunai hanya membantu meningkatkan konsumsi energi dan beberapa pangan strategis.
Keyword: covid-19, food consumption, income shock, sosial assistance, strategic food

Judul: Estimation of Income Shock Impact on Household Food Consumption in Bogor District and City
Abstrak: Salah satu dampak dari kebijakan Pembatasan Sosial Berskala Besar (PSBB) untuk menanggulangi penyebaran Covid-19 di Indonesia adalah income shock yang terjadi pada setiap golongan masyarakat, terutama rumah tangga berpendapatan rendah. Income shock ini berpotensi menurunkan kuantitas dan kualitas konsumsi pangan rumah tangga. Penelitian ini bertujuan untuk mengestimasi dampak income shock yang disebabkan oleh pandemi Covid-19 terhadap konsumsi pangan rumah tangga di Kabupaten dan Kota Bogor. Desain penelitian menggunakan desain studi deskriptif kuantitatif dengan data dasar Susenas 2017. Simulasi dilakukan dengan memasukkan model persamaan regresi pendapatan dengan konsumsi pangan rumah tangga. Hasil analisis menunjukkan adanya penurunan kategori Tingkat Kecukupan Energi (TKE) dan Tingkat Kecukupan Protein (TKP), terutama pada rumah tangga berpendapatan rendah setelah disimulasikan terkena income shock -10%, -20%, dan -30%. Pada rumah tangga berpendapatan rendah, jenis pangan strategis yang bersifat elastis atau mewah antara lain jagung, daging ayam, daging sapi, dan susu mengalami penurunan konsumsi yang signifikan. Bantuan Pangan Non-Tunai (BPNT) lebih signifikan meningkatkan kategori TKE dan TKP, serta pangan strategis, dibandingkan Bantuan Langsung Tunai (BLT). Kebijakan pemerintah berupa bantuan sosial, bisa dipertahankan dengan eksekusi yang lebih tepat sasaran., The impact of the semi-lockdown policy to tackle the spread of Covid-19 in Indonesia is an income shock that occurs in every class of society, especially lowincome households. This income shock potentially reduces household quantity and quality food consumption. This study aims to estimate the impact of the income shock caused by the Covid-19 pandemic on household food consumption in Bogor Regency and City. The research design uses a quantitative descriptive study with the Susenas 2017 as the basic data. The simulation starts by including an income on regression equation model with household food consumption. The results show that there is a decline in the categories of energy and protein adequacy percentage, especially in low-income households after being simulated with an income shock of -10%, -20%, and -30%. Low-income households also found some strategic foods are elastic or luxurious such as corn, chicken, beef, and milk, which encounter significant decrease in consumption. Food assistance is more significant increasing the categories of Energy and Protein Adequacy, as well as strategic food, than cash assistance. Government policies, such as social assistance, can be maintained with more precise execution.
Keyword: energy and protein adequacy, household consumption, income shock, strategic foods

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