Judul: Implementasi dan Evaluasi Sistem Zonasi Menggunakan Pathogen Environmental Monitoring (PEM) di PT Essence Indonesia – IFF
Abstrak: Penyebaran patogen dalam bahan pangan menjadi fokus yang perlu diwaspadai. Hal ini dikarenakan adanya patogen dalam bahan atau produk pangan akan memberikan dampak yang cukup besar dalam segi kesehatan maupun ekonomi baik bagi konsumen maupun produsen sendiri. Pemantauan dan monitoring terhadap patogen sangat diperlukan sebagai tindakan pencegahan kontaminasi silang pada produk pangan. Zonasi merupakan suatu konsep pembagian area produksi di dalam suatu industri berdasarkan prosedur kebersihan, praktik kerja dan pengendalian arah pergerakan pekerja, peralatan dan bahan untuk melindungi produk dari potensi bahaya yang berasal dari lingkungan industri dan sekitarnya. Program monitoring lingkungan atau Pathogen Environmental Monitoring (PEM) diperlukan untuk memverifikasi keefektifan pengendalian patogen sebagai upaya mencegah kontaminasi silang dan mengevaluasi konsep zonasi yang diterapkan di suatu area industri. Prosedur pemantauan dalam PEM dilakukan di empat zona yang diklasifikasikan berdasarkan risiko terhadap penyebaran patogen. Empat zona tersebut yaitu, area non-zonasi (non-zoning area), zona normal (normal zone), zona berisiko medium (medium care zone) dan zona berisiko tinggi (high care zone). Pengambilan sampel dilakukan dengan menggunakan swab di beberapa titik di area produksi. Selanjutnya dilakukan pengujian pada sampel antara lain uji Salmonella, Listeria spp., Total Enterobacteriaceae (TEB), dan uji kualitas mikroba udara ruang produksi menggunakan uji angka lempeng total (ALT) dan angka kapang khamir (AKK). Pengujian Salmonella dan Listeria spp. menunjukkan hasil negatif per m2 di seluruh titik pengambilan sampel. Sedangkan uji Total Enterobacteriaceae (TEB) menunjukkan hasil pengujian <1 cfu/ m2. Selain itu, pengujian kualitas mikroba udara menunjukkan hasil di bawah batas maksimum standar yaitu <100 cfu/jam/m2. Penggunaan sistem zonasi dan evaluasi dengan program PEM memberikan hasil yang sesuai standar sebagai upaya pencegahan penyebaran patogen.
Keyword: patogen, monitoring, PEM, zonasi, sistem pengendalian mikroba

Judul: Evaluation of GMP Implementation and  Opportunities for Cross Contamination Packing Area in Chicken Sausage  Production at PT XYZ
Abstrak: Sistem keamanan pangan menjadi hal yang harus diperhatikan untuk menghasilkan produk yang aman dan bermutu. PT XYZ merupakan salah satu industri sosis ayam yang telah mengimplementasikan GMP namun perlu dilakukan evaluasi. Proses packing memiliki peluang cemaran mikroba yang lebih tinggi sehingga perlu kaji ulang berupa evaluasi sanitasi alat maupun mesin, higiene karyawan, dan juga lingkungan. Penelitian ini bertujuan mengevaluasi penerapan GMP di PT XYZ dan peluang cross contamination sehingga didapatkan saran perbaikan sesuai standar aturan. Evaluasi penerapan GMP dilakukan dengan beberapa tahap yaitu pengumpulan data, analisis data, dan saran perbaikan. Evaluasi peluang cross contamination area packing dilakukan dengan beberapa tahap yaitu evaluasi sumber-sumber cross contamination, evaluasi efektivitas sanitasi, dan saran perbaikan. Hasil evaluasi penerapan GMP di PT XYZ menunjukkan tingkat penerapan GMP sebesar 81,76% dan termasuk dalam kategori penerapan GMP level III. Temuan teridentifikasi terdiri dari 2 temuan minor, 23 temuan mayor dan 6 temuan kritis berdasarkan checklist perdirjen. Perlu perbaikan lebih lanjut agar meningkatkan level penerapan dan keamanan serta standar kualitas produk. Evaluasi peluang cross contamination area packing menunjukkan salah satu sumber kontaminasi yaitu sanitasi dan higiene yang yang masih kurang baik dan tidak konsisten sehingga perlu perbaikan dan pengendalian dengan ketat proses sanitasi untuk menurunkan peluang cross contamination di area packing., The food safety system is something that must be considered to produce the safe and quality products. PT XYZ is one of the chicken sausage industries that has implemented GMP but needs to be evaluated. The packing process has a higher chance of microbial contamination, so it needs to be reviewed in the form of an evaluation of the sanitation of tools and machines, employee hygiene, and the environment. This study aims to evaluate the application of GMP at PT XYZ and the opportunities of cross contamination so that suggestions for improvement are obtained according to regulatory standards. Evaluation of the implementation of GMP is carried out in several stages, that is data collection, data analysis, and suggestions for improvement. Evaluation of cross contamination in the area packing opportunities is carried out in several stages, that is evaluation of sources of cross contamination, evaluation of sanitation effectiveness, and suggestions for improvement. The results of the evaluation of the implementation of GMP in PT XYZ showed that GMP implementation level of 81,76% and belonged to the category of level III implementation. The identified findings consisted of 2 minor findings, 23 major findings, and 6 critis findings with perdirjen checklist. Further improvements are needed to improve the level of application and safety as well as product quality standards. Evaluation of cross contamination opportunities in the packing area showed that one source of contamination, sanitation and hygiene, is still not good and not consistent, so it is necessary to improve and strictly control the sanitation process to reduce cross contamination opportunities in the packing area.
Keyword: GMP, food safety, sanitation, chicken sausage

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