Judul: Penyelesaian Cutting Stock Problem Satu Dimensi Menggunakan Metode Branch and Bound
Abstrak: Kain batik katun merupakan bahan utama yang biasa digunakan untuk membuat baju seragam keluarga. Pemotongan bahan kain batik haruslah menyesuaikan dengan kebutuhan keluarga tersebut. Oleh karena itu, pemotongan bahan kain batik perlu direncanakan agar mendapatkan hasil yang optimal untuk meminimumkan sisa bahan yang terbuang. Penelitian ini bertujuan untuk mencari pola pemotongan bahan seragam keluarga yang dapat meminimumkan sisa hasil pemotongan satu dimensi pada kain batik katun yang diperoleh menggunakan metode branch and bound serta mencari solusi yang optimal menggunakan bantuan software Lingo 11.0. Solusi yang diperoleh merupakan kombinasi pola pemotongan bahan kain yang optimal sehingga meminimumkan sisa hasil pemotongan. Model diimplementasikan pada masalah pemotongan stok bahan kain batik katun menggunakan bantuan bahasa pemrograman Python 3.9.5 dan software Lingo 11.0 yang memperlihatkan bahwa sisa hasil pemotongan sebesar 2,95% dari total bahan yang digunakan., Cotton batik cloth is the main material that is usually used in making family attires. The cloth's cut must be suitable with the family's requirement. Because of that, the cutting process must be planned carefully to give the optimal cut to minimalize the material wasted. This research is intended to find the cutting pattern for family attire material that could minimalize the one-dimensional cut on cotton batik cloth using the branch and bound method whilst finding an optimal solution using software Lingo 11.0. The produced solution would be optimal combinations of cutting patterns on the cloth so that the material leftover is minimal. The model is applied to the cutting stock problem using Python 3.9.5 and software Lingo 11.0 shows that the leftover and profit from the cutting process would be 2.95% of the total material used.
Keyword: branch and bound, cutting stock problem, optimization

Judul: Penyelesaian Cutting Stock Problem Dua Dimensi Menggunakan Pattern Generation Technique
Abstrak: Cutting Stock Problem (CSP) dua dimensi adalah suatu permasalahan pemotongan barang (item) yang berfokus pada dua sisi pemotongan yaitu anjang dan lebar. Pemotongan yang dilakukan bertujuan untuk meminimumkan sisa hasil pemotongan yang didapatkan. Salah satu metode dalam pemotongan CSP dua dimensi adalah pattern generation. Penelitian ini bertujuan untuk mendapatkan pola pemotongan optimal menggunakan pattern generation yang meminimalkan sisa hasil pemotongan kain di RB GROUP yang diimplementasikan menggunakan bantuan Excel dan software optimisasi Lingo 18.0. Hasil yang diperoleh untuk meminimumkan sisa pemotongan kain rol pada RB GROUP dapat dilakukan dengan memotong 2 kain rol berukuran 50 m × 1.5 m dengan pola 1633 yaitu 129 celana pendek ukuran XL, 84 ukuran L, dan 38 ukuran M, serta pola 1653 dengan 129 celana pendek ukuran XL, 51 ukuran L, dan 72 ukuran M. Kombinasi tersebut menghasilkan sisa pemotongan sebesar 14.81% dari total kain rol yang digunakan. Persentase tersebut lebih kecil 2.83 % dari persentase sisa pemotongan yang dilakukan oleh RB GROUP., The two-dimensional Cutting Stock Problem (CSP) is a problem of cutting items that focuses on two cutting dimensions: length and width. The cutting is aimed at minimizing the resulting of leftover cutting. One of the methods for solving the two-dimensional CSP is pattern generation. This research aims to obtain optimal cutting patterns using pattern generation to minimize the leftover fabric in RB GROUP's cutting process, implemented with the assistance of Excel and Lingo 18.0 optimization software. The results obtained indicate that to minimize the leftover fabric in roll cutting at RB GROUP, it is possible to cut 2 rolls of fabric with dimensions of 50 m × 1.5 m using pattern 1633, consisting of 129 XL-sized shorts, 84 L-sized shorts, and 38 M-sized shorts, as well as pattern 1653, consisting of 129 XL-sized shorts, 51 L-sized shorts, and 72 M-sized shorts. This combination results in a leftover fabric of 14.81% of the total fabric used. This percentage is 2.83% smaller than the leftover fabric percentage achieved by RB GROUP.
Keyword: cutting stock, leftover cutting, optimal, pattern generation

Judul: Evaluation of Influenza Antibody Titers in Serum and Egg Yolk of Layers Vaccinated with Influenza Vaccines.
Abstrak: Influenza belongs to the Orthomyxoviridae family which causes upper and lower respiratory tract infection. The aim of this study was to evaluate influenza-A specific antibody titers from serum and egg yolk of hens vaccinated with quadrivalent influenza vaccines. Three Hy-line Brown layers were vaccinated with quadrivalent influenza type A and B inactivated vaccines. Vaccination was carried out three times at a dose of 0.25 ml/chicken via the intramuscular route. The first vaccination was carried out at 24 weeks of age, then boosters were performed at 28 and 32 weeks of age. Serum and egg yolk were collected every week for 20 weeks since the first vaccination. Influenza A H3N2 and H1N1 antibody titers were determined using hemagglutination-inhibition (HI) test and agar-gel-precipitation (AGP) test. Influenza-A H3N2 and H1N1 specific antibodies were detected in both serum and egg yolk from the first to twenty weeks after the initial vaccination. Highest HI geometric mean titer (GMT) of H1N1 antibody reached 26.67 HIU at nine weeks post first vaccination (p.f.v), while H3N2 antibody reached 26 HIU at six weeks p.f.v. Our result showed that influenza antibodies can be produced in layers using quadrivalent vaccines and layer chickens are able to produce equivalent antibody levels for each influenza subtype.
Keyword: antibody, egg yolk, influenza, layer chickens, serum