Judul: Solving 0-1 Knapsack Problem Using Migrating Birds Optimization Algorithm and Particle Swarm Optimization Algorithm
Abstrak: Masalah knapsack merupakan permasalahan optimisasi kombinatorial yang diklasifikasikan sebagai NP-complete problem. Tujuannya adalah untuk memperoleh keuntungan maksimum tanpa melebihi kapasitas knapsack dengan objek yang dipilih. Ada beberapa metode yang dikembangkan untuk permasalahan ini, salah satunya adalah metode meta-heuristic. Pada karya ilmiah ini, digunakan metode meta-heuristic migrating birds optimization (MBO) dan particle swarm optimization (PSO) untuk menyelesaikan masalah knapsack. Hasil yang diperoleh menunjukkan bahwa algoritme MBO menghasilkan keuntungan yang relatif lebih besar dibandingkan algoritme PSO., Knapsack problem is a combinatorial optimization problem which is classified as an NP-complete problem. Its aim is to achieve maximum benefit without exceeding the capacity of the knapsack with the selected objects. There are several methods developed for this problem, one of them is a meta-heuristic method. In this manuscript, migrating birds optimization (MBO) and particle swarm optimization (PSO) as meta-heuristic methods will be used to solve the knapsack problem. The result obtained shows that the MBO algorithm produces a relatively larger benefit than the PSO algorithm.
Keyword: knapsack problem, meta-heuristic method, migrating birds optimization, particle swarm optimization

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: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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