Judul: Penyelesaian Cutting Stock Problem Satu Dimensi Menggunakan Algoritme Particle Swarm Optimization
Abstrak: Cutting stock problem (CSP) merupakan permasalahan pemotongan persediaan yang sering dijumpai di banyak industri. Tujuannya untuk mendapatkan sisa pemotongan seminimum mungkin, namun tetap memenuhi permintaan pelanggan. Ada beberapa metode yang dapat digunakan untuk menyelesaikan permasalahan ini. Pada karya ilmiah ini, digunakan metode heuristik particle swarm optimization (PSO) sebagai penyelesaian masalah CSP. Pada tahap pertama penulis menentukan kombinasi pola pemotongan yang mungkin dapat digunakan dengan bantuan bahasa pemrograman Python. Selanjutnya, dibuat model matematis dan kendala sesuai pola yang tersedia. Kemudian, algoritme PSO digunakan untuk menentukan kombinasi pola potongan supaya menghasilkan sisa pemotongan yang paling sedikit. Diawali dengan inisialisasi parameter yang digunakan. Kemudian setelah diimplementasikan, menghasilkan kombinasi pola pemotongan rol kertas yang optimum yaitu sebanyak tiga rol untuk pola satu, 29 rol untuk pola 23, enam rol untuk pola 27 dan 29 rol untuk pola 32., Cutting stock problem (CSP) is an inventory cutting problem that is often encountered in many industries. The goal is to get the remaining cutting to a minimum, while still meeting customer demands. There are several methods that can be used to solve this problem. In this scientific paper, the heuristic particle swarm optimization (PSO) method is used to solve the CSP problem. In the first stage the author determines the possible combination of cutting patterns that can be used with the help of the Python programming language. Next, a mathematical model and constraints are made according to the available patterns. Then, the PSO algorithm is used to determine the combination of cut patterns in order to produce the least amount of cutting residue. It begins with the initialization of the parameters used. Then after it was implemented, it resulted in the optimum combination of aluminum roller cutting patterns as many as three rolls for pattern one, 29 rolls for pattern 23, six rolls for pattern 27 and 29 rolls for pattern 32.
Keyword: cutting stock problem, particle swarm optimization, trim loss

Judul: Masalah Cutting Stock Satu Dimensi yang Meminimumkan Banyaknya Pola Berbeda
Abstrak: Cutting stock problem (CSP) merupakan masalah menentukan cara terbaik agar objek yang berukuran besar dapat dipotong menjadi objek yang berukuran lebih kecil sesuai permintaan dan sisa yang minimum. Namun selain bertujuan meminimumkan sisa bahan, ada masalah lain dalam CSP yaitu meminimumkan banyaknya pola pemotongan yang berbeda. Hal ini disebabkan karena adanya biaya setup setiap suatu pola berbeda dipotong. Karya ilmiah ini bertujuan untuk mendapatkan banyaknya pola berbeda yang optimal pada suatu masalah agar biaya pemotongan minimum. Suatu masalah pembangunan 12 pendopo akan dimodelkan ke dalam cutting stock satu dimensi yang meminimumkan banyaknya pola berbeda dalam bentuk pemrograman linear. Model ini diselesaikan dengan algoritme column generation dan menggunakan perangkat lunak Lingo 18.0. Hasil optimal yang diperoleh adalah lima pola pemotongan besi yang berbeda dengan biaya pemotongan besi berupa pendekatan sebesar Rp270.513.000,00. Jumlah total stok besi yang digunakan adalah 93 batang besi baja yang terdiri dari pola 5 sebanyak 48 besi, pola 7 sebanyak 3 besi, pola 8 sebanyak 21 besi, pola 11 sebanyak 15 besi, dan pola 12 sebanyak 6 besi., Cutting stock problem (CSP) is a problem to determine the best way so that the large objects can be cut into smaller objects on demand and with minimum waste. However, besides of minimize material waste, there is another problem with CSP which is to minimize different cutting patterns. This is because there will be setup costs for each different pattern are cut. This scientific work aims to obtain the optimal number of different patterns on a problem so the cutting costs are minimum. A problem about the construction of 12 pavilions will be modeled into a onedimensional cutting stock that minimizes the number of different patterns in linear programming. This model is solved by column generation algorithm and using Lingo 18.0 software. The optimal results obtained are five different iron cutting patterns with the cost of iron cutting in approach is Rp270.513.000,00. The total amount of iron stock used is 93 iron bars, consisting of 48 bars of 5th pattern, 3 bars of 7th pattern, 21 bars of 8th pattern, 15 bars of 11th pattern, and 6 bars of 12th pattern.
Keyword: column generation, cutting stock problem, different pattern, linear programming, setup cost

Judul: Profil Antibodi IgM dan IgG pada Beruk (Macaca nemestrina) setelah Diinfeksi Virus Dengue Serotipe-3 (DEN-3) melalui Rute Intravena
Abstrak: The aim of this study was to detect IgM and IgG in pig-tailed macaques (Macaca nemestrina) primarily innoculated by Dengue virus serotype-3 (DEN-3) by intravenous route. A total of 84 plasma samples were examined in the study. Plasma samples were taken on day 0 before infection, followed by plasma collections on day 1 through day 13 post infection. The obtained plasma samples were analyzed using indirect ELISA test. The results showed the increasing titer of IgM started on day-3 post infection with its peak occurred on day 11 post infection and started to decline afterward; while the IgG titer started to increase on day 6 or day 7 post infection and continue to increase until the day 13 post infection. These results showed that in a primary infection of DEN-3 byintravenous route, the tendency of IgM titer increase was higher than the IgG titer increase; also shown that the IgM titer increase was occured earlier than IgG. The profile of IgM and IgG antibodies is outlined in this study.
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