Judul: RISIKO PAPARAN KADMIUM DARI COKELAT BATANG PADA KONSUMEN DI INDONESIA
Abstrak: Cadmium is a common contaminant found in cocoa derivative products such as chocolate bars because it is carried away from the cocoa beans. The popularity of chocolate bars among Indonesian consumers may pose a health risk due to cadmium (Cd) content in chocolate bars. The present study aimed to obtain the cadmium (Cd) content in chocolate bars and its dietary exposure to the Indonesia population. Samples of 10 different varieties of chocolate bars were collected from markets in Indonesia and analyzed for their Cd content using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). The results show that Cd content in chocolate bars ranged between 0.00012 mg/kg to 0.12 mg/kg with the highest content was found in one variant of sweet dark chocolate bar. None of samples contained Cd above the maximum limits of Cd (0.5 mg/kg in chocolate bar products) as regulated by NADFC. The highest average consumption of chocolate bars was found in adolescence (13-18 years), followed by toddler (6-59 months) and children (5-12 years). The highest P95 exposure to Cd from chocolate bars was found in toddler (6-59 months), followed by children (5-12 years), 0.28733 μg/kg bw/day and 0.17846 μg/kg bw/day. The P95th exposures to Cd from chocolate bars in all age groups did not exceed its Provisional Tolerably Monthly Intake (PTMI), indicating that the exposure to Cd through chocolate bar products do not pose any potential risk to human health
Keyword: 

Judul: Sensory Optimization of Chocolate Bar Products from XYZ Industry using CATA, RATA, and JAR Methods
Abstrak: Indonesia is a major player in the global cocoa production and export industry, yet domestic chocolate consumption remains low, averaging only 0.10 kg per person per year compared to higher consumption rates in Europe. This low consumption is attributed to subpar chocolate products and the consumer perception that chocolate is an unhealthy food associated with obesity. XYZ industry, based in Magelang Regency, Central Java, aims to support local cocoa farmers and produce healthier, vegan chocolate bars with functional benefits. However, their current chocolate bar products do not consistently meet consumer taste preferences, despite their health advantages. Sensory evaluation was conducted on 12 chocolate bar products using Check-All-That-Apply (CATA), Rate-All-That-Apply (RATA), and Just-About-Right (JAR) methods to understand consumer perceptions and preferences. CATA identified Solid Energy Chocolate as the ideal product due to its nutty and cereal attributes. RATA analysis provided detailed sensory profiles, revealing that Sea Salt & Almond, Lactation Chocolate, and Solid Energy were most preferred by consumers. JAR method results indicated that the majority of attributes in the Solid Energy Chocolate variant were considered “too little,” but the results were inconclusive due to panelist misinterpretation of intensity scales. Sensory optimization needs to be performed on 6 chocolate bar variants that has the percentage of consumer’s satisfaction low, to better meet consumer preferences., Indonesia adalah pemain utama dalam industri produksi dan ekspor kakao global, namun konsumsi cokelat domestik tetap rendah, rata-rata hanya 0.10 kg per orang per tahun dibandingkan dengan tingkat konsumsi yang lebih tinggi di Eropa. Konsumsi yang rendah ini disebabkan oleh produk cokelat yang kurang memadai dan persepsi konsumen bahwa cokelat adalah makanan tidak sehat yang berkaitan dengan obesitas. Industri XYZ, yang berbasis di Kabupaten Magelang, Jawa Tengah, bertujuan untuk mendukung petani kakao lokal dan memproduksi cokelat batangan yang lebih sehat, vegan, dan memberikan manfaat fungsional. Namun, produk cokelat batangan mereka saat ini tidak secara konsisten memenuhi preferensi rasa konsumen, meskipun memiliki keunggulan kesehatan. Evaluasi sensori dilakukan pada 12 produk cokelat batangan menggunakan metode Check-All-That-Apply (CATA), Rate-All-That-Apply (RATA), dan Just-About-Right (JAR) untuk memahami persepsi dan preferensi konsumen. CATA mengidentifikasi Solid Energy Chocolate sebagai produk ideal karena atributnya yang nutty dan sereal. Analisis RATA memberikan profil sensori yang mendetail, mengungkapkan bahwa varian Sea Salt & Almond, Lactation Chocolate, dan Solid Energy adalah yang paling disukai oleh konsumen. Hasil metode JAR menunjukkan bahwa mayoritas atribut pada varian Solid Energy Chocolate dianggap “terlalu sedikit,” namun hasil ini tidak konklusif karena kesalahan interpretasi intensitas oleh panelis. Optimalisasi sensori dirasa perlu dilakukan pada 6 varian cokelat batangan yang memiliki persentase kepuasan konsumen rendah, agar dapat memenuhi preferensi konsumen.
Keyword: sensory evaluation, CATA, RATA, JAR, Chocolate bar, Check-all-that-apply, Rate-all-that-apply, Just-about-right

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