Judul: Pengaruh Transformasi Perdesaan dan Perubahan Iklim terhadap Ketahanan Pangan di Kawasan Indonesia Timur
Abstrak: Meningkatnya suhu permukaan bumi sebagai dampak dari perubahan iklim diperkirakan akan meningkatkan intensitas bencana alam yang akan mengancam produksi pertanian dan memperparah kerawanan pangan. Bagi negara yang rentan terhadap bencana alam seperti Indonesia, ancaman ini perlu ditanggapi dengan serius. Terlebih Kawasan Indonesia Timur yang mayoritas wilayahnya terdiri dari perdesaan dan masih bergantung dengan aktivitas pertanian sangat rentan terhadap perubahan dalam sistem iklim ini. Mengetahui hal ini, transformasi perdesaan sebagai strategi adaptasi perlu menjadi prioritas untuk menjaga dan meningkatkan ketahanan pangan di Kawasan Indonesia Timur. Penelitian ini ditulis dengan tujuan untuk mengetahui bagaimana transformasi perdesaan dan perubahan iklim mempengaruhi kondisi ketahanan pangan di Kawasan Indonesia Timur. Metode analisis yang digunakan dalam penelitian ini adalah analisis statistik deskriptif dan regresi data panel statis. Hasil penelitian yang ditemukan menunjukkan transformasi perdesaan yang diproksikan dengan share tenaga kerja di sektor non-pertanian dan indeks risiko bencana sebagai proksi dari perubahan iklim dengan signifikan mempengaruhi ketahanan pangan di Kawasan Indonesia Timur. Selain itu, faktor sosial-ekonomi lainnya seperti tingkat kemiskinan, rata-rata lama sekolah perempuan, dan PDRB per kapita juga mempengaruhi ketahanan pangan dengan signifikan., The increasing temperature of the earth's surface as a result of climate change is expected to increase the intensity of natural disasters that will threaten agricultural production and exacerbate food insecurity. For countries that are proned to natural disasters like Indonesia, this threat needs to be taken seriously. Especially Eastern Indonesia, where the majority of the areas consists of rural and is still dependent on agricultural activities, is very vulnerable to changes in the climate system. Knowing this, rural transformation as an adaptation strategy needs to be a priority to maintain and improve food security in Eastern Indonesia. This research was written with the aim of knowing how rural transformation and climate change affect food security in Eastern Indonesia. The analytical methods used in this research are descriptive statistical analysis and static panel data regression. The results of the study found that the share of labor in the non- agricultural sector as a proxy for rural transformation and the disaster risk index as a proxy for climate change significantly affect food security in Eastern Indonesia. In addition, other socio-economic factors such as the poverty rate, the average length of school year of women, and GRDP per capita also significantly affect food security.
Keyword: Climate Change, Food Security, Panel Data, Rural Transformation

Judul: Regional Rural Transformation in Indonesia Base on Low Value Agriculture Commodities
Abstrak: Transformasi perdesaan menggambarkan pergeseran fokus produksi dari komoditas pertanian bernilai rendah menuju bernilai tinggi. Berdasarkan data share PDRB komoditas pertanian bernilai rendah di Indonesia mengalami penurunan dibandingkan komoditas pertanian bernilai tinggi, sehingga mengindikasikan terjadinya proses transformasi perdesaan di Indonesia. Penelitian ini bertujuan mengetahui kondisi komoditas pertanian bernilai rendah di Indonesia dengan periode waktu multi tahunan dari tahun 2000 sampai 2018 dan mengetahui pengaruh institusi, kebijakan, dan investasi terhadap transformasi perdesaan di Indonesia berdasarkan komoditas pertanian bernilai rendah. Metode yang digunakan dalam penelitian ini adalah analisis deskriptif dan analisis regresi data panel dengan menggunakan data 25 provinsi di Indonesia dengan periode waktu multi tahunan dari tahun 2000 sampai 2018. Hasil estimasi data panel pada penelitian ini menunjukan variabel fasilitas keuangan (koperasi), fasilitas pasar, PMA sektor pertanian, PMDN sektor pertanian, dan fasilitas kesehatan (rumah sakit) diketahui berpengaruh secara negatif dan signifikan terhadap share PDRB pertanian subsektor tanaman pangan. Variabel luas lahan, dana desa, dan tenaga kerja subsektor pangan berpengaruh positif dan signifikan terhadap share PDRB pertanian subsektor tanaman pangan. Kata kunci : komoditas pertanian bernilai rendah, subsektor pangan, transformasi perdesaan, Rural transformation illustrates the transition of low value agricultural commodities to high value comodities. Based on data, low value agricultural comodities in Indonesia had decreased compared to high value commodities, indicates of rural transformation in Indonesia. This studied aims to determine the condition of low value commodities in Indonesia with a multi-year period from 2000 to 2018 and to determine the influence of institutions, policies, and investments on rural transformation in Indonesia based on low value commodities. This study used descriptive analysis and panel data regression analysis method using data from 25 provinces in Indonesia with a multi-year period from 2000 to 2018. The estimation results of panel data in this studied showed the variables of financial facilities, market facilities, PMA in the agricultural sector, PMDN in the agricultural sector, and health facilities were known to have a negative and significant effect on the share of PDRB of the food crop agriculture sub-sector. The variables of land area, dana desa, and labor in the food sub-sector had a positive and significant impact on the share of PDRB of the food crop agriculture sub-sector Keywords: food crop agriculture sub-sector, low value agricultural comodities, rural transformation
Keyword: komoditas pertanian bernilai rendah, subsektor pangan, transformasi perdesaan

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