Judul: Pengembangan model penyimpanan buah tropika dalam atmosfir terkendali (CA) : kasus durian
Abstrak: Durian merupakan salah satu buah tropika yang memiliki nilai komersial tinggi. Produksi durian di Indonesia meningkat dari 228 668 ton dalam tahun 1993 menjadi 459 007 ton dalarn tahun 1997. Volume ekspor durian dalam tahun 1993 mencapai 331.317 ton (atau hanya 0.145% dari produksi) dengan nilai US$ 273 300, yang meningkat menjadi 695.614 ton (0.152% dari produksi) dengan nilai US$ 642 822 dalarn tahun 1997 (Anonymous, 1998). Namun demikian durian memiliki kendala yakni umur simpan yang singkat setelah dipetik 3-7 hari. Kerusakan selama penyimpanan diakibatkan oleh proses fisiologik seperti respirasi dan transpirasi.
Keyword: 

Judul: Carbon Stock Estimation of Durian Plantations using Remote Sensing Techniques
Abstrak: Durian (Durio zibethinus) merupakan salah satu komoditas dengan produksi yang terus meningkat setiap tahunnya, menyebabkan adanya peralihan fungsi lahan hutan, dan dapat menurunkan stok karbon wilayah tersebut. Penelitian ini bertujuan menjelaskan kondisi stok karbon daerah perkebunan durian, menganalisis kondisi vegetasi daerah perkebunan durian melalui indeks NDVI, serta menentukan kesesuaian model estimasi stok karbon dari NDVI yang telah ada sebelumnya. Penelitian dilakukan selama bulan Januari – Mei 2024. Analisis dilakukan dengan beberapa tahapan, yaitu analisis NDVI dengan data satelit Landsat 8 (band 4 dan band 5), evaluasi kesesuaian 9 model estimasi stok karbon yang ada (Lombok Barat, Banyumas, dan Wonosobo) melalui nilai RMSE dan korelasi pearson, serta penerapan model terbaik untuk estimasi stok karbon 2017 – 2023. Hasil analisis menunjukkan bahwa data lapangan stok karbon di perkebunan durian cenderung mengalami peningkatan seiring meningkatnya umur pohon. NDVI di wilayah perkebunan durian bervariasi pada rentang 0,2911 – 0,3929. Evaluasi model stok karbon menghasilkan galat yang cukup besar dengan korelasi pearson yang lemah disebabkan oleh komoditas yang berbeda. Penerapan model terbaik, C = 422.33(NDVI)^3,0547 menunjukkan adanya kecenderungan peningkatan stok karbon dari tahun 2017 – 2023., The production of durian (Durio zibethinus) has been increasing annually, resulting in the conversion of forest land functions and a reduction in the carbon stock of the region. This research aims to elucidate the carbon stock status of durian plantations, analyze the vegetative condition of durian plantations through the NDVI index, and ascertain the suitability of existing carbon stock estimation models based on NDVI. The research was conducted over the period from January to May 2024. The analysis was conducted in several stages. Initially, NDVI analysis was performed using Landsat 8 satellite data (bands 4 and 5). Subsequently, the suitability of nine existing carbon stock estimation models was evaluated (West Lombok, Banyumas, and Wonosobo) through RMSE and Pearson correlation values. Finally, the most suitable model was applied for carbon stock estimation from 2017 to 2023. The results of the analysis indicate that the field data of carbon stocks in durian plantations tend to increase with increasing tree age. The NDVI in the durian plantation area exhibited a range of 0.2911 to 0.3929. The evaluation of the carbon stock model yielded considerable errors with a weak Pearson correlation due to the differing commodities. The application of the optimal model, C = 422.33(NDVI)^3.0547, demonstrated an increasing trend in carbon stocks from 2017 to 2023.
Keyword: durian, NDVI, pemodelan, stok karbon

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