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"The contents of this thesis are the development of 3D simulator for visualizing Particle Swarm Optimization algorithm for Multi Odor Source Localization using Open Dynamics Engine, and Dynamic Niche-PSO as modification of MPSO algorithm from previous research [1]. The 2D version of this MPSO is made in previous research. This 3D physic modeling has a purpose to reduce gap between software and hardware in the real world. One of chapters is explaining how to make the model of robots, plumes and its sources, and field with Open Dynamics Engine. Continued with chapter explaining how to use the GUI of this simulator. Dynamic Niche-PSO algorithm proposed in this research has a purpose to refine the weakness of previous algorithm where 2 niches (group of agent) or more still have a probability to move toward the same odor source. There is newly introduced robot in this Dynamic Niche-PSO algorithm called main robot which has attract area. In this Dynamic Niche-PSO also a neutral robot or a charge robot could become a member of another niche if it entered the attract area of main robot of this other niche.

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Isi tesis ini mengenai pembuatan simulator 3D dari algoritma pencarian Particle Swarm Optimization untuk pencarian banyak sumber asap dengan menggunakan Open Dynamics Engine dan mengenai Dynamic Niche-PSO yang adalah algoritma baru sebagai modifikasi algoritma MPSO dari penelitian sebelumnya [1]. Versi simulator 2D untuk PSO ini telah dibuat pada penelitian sebelumnya. Pemodelan fisik 3D ini bertujuan untuk mengurangi gap antara perangkat lunak dan perangkat keras di dunia nyata. Salah satu bab adalah bab yang menjelaskan pembuatan model robot, asap dan sumbernya, dan medan dengan Open Dynamics Engine. Dilanjutkan dengan bab tentang cara pemakaian GUI simulator ini. Algoritma Dynamic Niche-PSO yang diajukan pada penelitian ini bertujuan untuk memperbaiki kelemahan algoritma PSO sebelumnya dimana 2 niche (kelompok agen) atau lebih masih ada kemungkinan untuk menuju sumber asap yang sama. Pada Dynamic Niche-PSO ini diperkenalkan robot baru, yaitu robot utama yang mempunyai area ketertarikan. Pada Dynamic Niche-PSO ini juga robot netral dan robot bermuatan dapat berpindah keanggotan dari satu niche ke niche yang lain apabila memasuki attract area dari robot utama niche tersebut. "

"Isi tesis ini mengenai pembuatan simulator 3D dari algoritma pencarian Particle Swarm Optimization untuk pencarian banyak sumber asap dengan menggunakan Open Dynamics Engine dan mengenai Dynamic Niche-PSO yang adalah algoritma baru sebagai modifikasi algoritma MPSO dari penelitian sebelumnya [1]. Versi simulator 2D untuk PSO ini telah dibuat penelitian sebelumnya ini. Pemodelan fisik 3D ini bertujuan untuk mengurangi gap antara perangkat lunak dan perangkat keras di dunia nyata.Salah satu bab adalah bab yang menjelaskan pembuatan model robot, asap dan sumbernya, dan medan dengan Open Dynamics Engine. Dilanjutkan dengan bab tentang cara pemakaian GUI simulator ini.Algoritma Dynamic Niche-PSO yang diajukan pada penelitian ini bertujuan untuk memperbaiki kelemahan algoritma PSO sebelumnya dimana 2 niche (kelompok agen) atau lebih masih ada kemungkinan untuk menuju sumber asap yang sama. Pada Dynamic Niche-PSO ini diperkenalkan robot baru, yaitu robot utama yang mempunyai arca ketertarikan. Pada Dynamic Niche-PSO ini juga robot netral dan bermuatan dapat berpindah keanggotaan dari satu niche ke niche yang lain apabila memasuki arca ketertarikan atau attract area dari robot utama niche yang lain ini.

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The contents of this thesis are the development of 3D simulator for visualizing Particle Swarm Optimization algorithm for multi odor source localization using Open Dynamics Engine, and Dynamic Niche-PSO as modification of MPSO algorithm from previous research [1]. The 2D version of this MPSO is made in previous research. This 3D modeling has a purpose to reducegap between Software and Hardware in the real world.

One of chapters is explaining about how to make the model of robots, plumes and its sources, and field with Open Dynamics Engine. Continued with chapter explaining about how to use the GUI of this simulator.

Dynamic Niche-PSO algorithm proposed in this research has a purpose to refine the weakness of previous algorithm where 2 niches (group of agents) or more still have a probability to move toward the same odor source. There is newly introduced robot in this Dynamic Niche-PSO algorithm called main robot which has an attract area. In this Dynamic Niche-PSO also a neutral robot or a charge robot could become a member of another niche if it entered the attract area of main robot of this other niche."

"Upaya pengembangan sistem deteksi kebocoran gas telah menjadi penelitian serius bagi banyak ahli di bidang komputasi, informatika dan fisika. Sistem deteksi gas menjadi kebutuhan mendesak saat ini mengingat banyaknya ancaman yang muncul dalam kehidupan masyarakat, seperti ancaman bom, kebocoran pipa gas, kebakaran hutan, dan lain sebagainya. Particle Swram Optimization (PSO) adalah salah satu algoritma yang handal untuk pencarian sumber gas. Penelitian ini akan menganalisa simulator 3D robot pencari sumber gas yang dibuat dengan menggunakan Open Dynamics Engine. Simulator ini merupakan pengembangan beberapa orang secara bertahap di mana terdapat beberapa variasi dalam implementasi algoritmanya. Penulis akan mencoba menganalisa kinerja setiap simulator ini. Riset robot pendeteksi gas ini dimulai oleh Wisnu Jatmiko yang berhasil mengembangkan sistem deteksi gas melalui modifikasi PSO dengan memanfaatkan mekanisme Detect and Response, penggunaan Charge Robot, dan pemanfaatan prinsip Wind Utilities. Pada penelitian selanjutnya, algoritma ini dikembangkan menjadi empat metode, yaitu metode penutupan sumber gas, metode peningkatan mekanisme DR-PSO dengan penambahan fase spread, metode pemanfaatan paralelisasi niche, dan metode penggunaan range global best.Penulis akan menganalisa performa robot dalam menutup semua kebocoran gas berdasarkan metode-metode tersebut. Analisa pertama dilakukan pada kasus dimana robot menggunakan metode penutupan sumber gas dan metode penigkatan mekanisme DR-PSO dengan penambahan fase spread namun belum mengenal paralel niche. Analisa kedua dilakukan pada kasus dimana robot menggunakan metode seperti pada analisa pertama namun dengan paralel niche. Analisa ketiga dilakukan pada kasus di mana robot menggunakan metode seperti pada analisa kedua namun dengan adanya tambahan sebuah robot yang menjadi pemimpin setiap niche.

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Developing a gas leakage detection system has become a serious research for many experts in the field of computing, informatics and physics. Gas detection system is an urgent need especially nowadays considering the threats that appear in people's lives, such as bomb threats,gas leaks, forest fires, and so forth. Particle Swarm Optimization (PSO) algorithm is one of the algorithm to search the source of the gas leak. This research will analyze the performance of 3D robot simulators that search source of gas leak. This simulator is built using the Open Dynamics Engine. This simulator is developed by some people which are differs in the implementation of algorithm. The author tries to analyze the performance of each simulator. Research on robotic that serve as gas detection started by Wisnu Jatmiko when he successfully developed gas detection systems through PSO using the Detect and Response mechanisms, the use of Charge Robot, and the principles of Wind Utilities. On further research, algorithms were developed into four methods, namely methods of closing the gas source, methods of increasing DR-PSO mechanism with the addition of phase spread, the utilization of parallelization niche methods, and methods using of global best range. The author will analyze the performance of all robots in the gas leak detection based on these methods. The first analysis is done on cases where the robot using the method of closing the gas method and the improving of DR-PSO mechanism with the addition of spread phase but have not implemented parallel niche. On second analysis, conducted on cases where robots use the method which is similar to first analysis but with a parallel niche implemented. On third analysis, conducted on cases where robot uses methods such as on the second analysis but with the addition of a robot or more which is being the leader of each niche."

"The 0-1 multidimensional knapsack problem (MKP) has been proven it belongs to difficult NP-har combinatorial optimization problems. There are various search algorithms based on population concept to solv these problems. the particle swarm optimization (PSO) technique is adapted in our stucy, which proposes a novel PSO algorithm, namely, the binary PSO based on surrogate information with proportional acceleration coefficients (BPSOSIPAC). the proposed algorithm was tasted on 135 benchmark problems from the OR-Library to validate and demonstrate the efficiency in solving multidimensional knapsack problems. The result were then compared with those in the other nine existing PSO algorithms. The simulation and evaluation result showed that the proposed algorithm, BPSOSIPAC, is superior to the of successful runs, average eror (AE) , mean absolute deviation, mean absolute percentage error, last error, standard deviation, best profit, mean profit, worst profit, AE of the best profit (%), AE of the mean profit deviaton. "

"Nowadays, the pursuance of sustainability obligates manufacturers to redesign products in order to reduce negative environmental impacts. However, only a few studies have simultaneously considered environmental sustainability and assemblability. To bridge this research gap, this study aimed to develop a redesign method based on modular product architecture. This method manages to support a sustainable product considering its materials, assembly sequence and line balance at initial design phase. This method begins with a current product analysis based on economic and environmental performances (i.e., total cost and CO2 emissions). Additionally, new materials and assembly methods are incorporated into redesigning a more sustainable product without compromising production performance. To ensure assemblability, the line balance of 60% is served as one of the constraints. This study applies the particle swarm optimization algorithm to calculate an optimal module organization along with assembly methods and assembly sequences. An air purifier case study is presented to demonstrate the benefits of the proposed method. As a result, the redesigned product can be more easily maintained during product usage and be recycled at the end of product life."

"The objective of this monograph is to provide a concise introduction tothe dynamics of systems comprised of charged small-scale particles. Flowing, small-scale, particles ("particulates'') are ubiquitous in industrial processes and in the natural sciences. Applications include electrostatic copiers, inkjet printers, powder coating machines, etc., and a variety of manufacturing processes. Due to their small-scale size, external electromagnetic fields can be utilized to manipulate and control charged particulates in industrial processes in order to achieve results that are not possible by purely mechanical means alone. A unique feature of small-scale particulate flows is that they exhibit a strong sensitivity to interparticle near-field forces, leading to nonstandard particulate dynamics, agglomeration and cluster formation, which can strongly affect manufactured product quality. This monograph also provides an introduction to the mathematically-related topic of the dynamics of swarms of interacting objects, which has gained the attention of a number of scientific communities. In summary, the following topics are discussed in detai l: (1) Dynamics of an individual charged particle, (2) Dynamics of rigid clusters of charged particles, (3) Dynamics of flowing charged particles, (4) Dynamics of charged particle impact with electrified surfaces and (5) An introduction to the mechanistic modeling of swarms. "

"Putusnya jaringan komunikasi sebagai dampak suatu bencana merupakan permasalahan yang perlu cepat diatasi agar tidak menimbulkan kerugian yang lebih besar. Komunikasi antara lokasi bencana dengan dunia luar menjadi sangat penting dalam menentukan tindakan yang tepat untuk meminimalisasi kerugian akibat bencana. Kajian penggunaan mobile robot otonom untuk menghubungkan menara-menara komunikasi yang terputus dapat menjadi solusi alternatif untuk mengatasi masalah ini. Dalam penelitian ini, penulis mengkaji beberapa algoritma perluasan jaringan dalam bentuk simulasi menggunakan Library Open Dynamic Engine. Library Open Dynamic Engine merupakan library yang telah menggunakan perhitungan fisika secara efisien dan teruji sehingga dapat mendekati keadaan dunia sebenarnya. Simulasi ini bertujuan untuk mendemontrasikan serta membandingkan bahwa algoritma ini dapat dikembangkan untuk menghubungkan menara komunikasi.

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The disconnection in communication networks as the impact of a disaster is a problem that needs to be addressed quickly in order to avoid greater losses. Communication between the disaster site with the outside world becomes very important in determining the appropriate action to minimize losses due to disasters. Study the use of autonomous mobile robots for connecting communication towers that was disconnected can be alternative solutions to address these issues. In this study, the authors examine some of the network expansion algorithm in the form of a simulation using Open Dynamics Engine library. Library of Open Dynamic Engine is a library that has used physics calculations in an efficient and tested so can approach the state of the real world. This simulation aims to demonstrate and compare that this algorithm can be developed to connect the communication towers."

" PSS (Power system stabilizer) telah digunakan secara luas untuk memperbaiki stabilitas sistem tenaga listrik modern. Dalam makalah ini diusulkan perancangan sistematik PSS dengan Particle Swarm Optimization (PSO) sebagai metode optimasi penalaan parameter PSS. Penalaan parameter PSS dilakukan untuk mendapatkan sistem tenaga listrik yang stabil dan teredam secara optimal. Kriteria optimal yang digunakan dalam proses penalaan parameter adalah indeks performansi Integral of Time multiplied by Absolute Error (ITAE). Performansi dariPSS ini diujikan pada sistem tenaga listrik mesin tunggal dibawah gangguan kecil, kondisi beban dan parameter tertentu. Hasil analisa nilaieigen dan simulasi menunjukkan bahwa osilasi sistem tenaga listrik dapat teredam secara optimal melalui penalaan PSS berbasis PSO ini. Hasil simulasi juga menunjukkan bahwa performansi dinamik PSS berbasis PSO lebih baik dibandingkan PSS yang ditala secara konvensional.

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AbstractPower system stabilizer (PSS) have been extensively used in modern power system for enhancing stability of the system. This paper presents a new systematic approach for the design of power systemstabilizer using PSO (Particle Swarm Optimization). The proposed approach employs PSO search for optimal setting of PSS parameters. The optimal criteria of the Integral of Time multiplied by AbsoluteError (ITAE) is used to search optimal setting. The performance of the proposed PSS under small disturbances, loading conditions and system parameters is tested. The eigenvalue analysis and simulationresults show the effectiveness of the PSO based PSS to damp out the system oscillations. It is found that the dynamic performance with the PSO based PSS shows improved results, over conventionally tunedPSS."

"Kompleksitas menuntut para peneliti untuk membuat kecerdasan buatan. Skripsi ini membahas tentang implementasi algoritma pencarian rute Swarm Intelligece pada sistem kontrol visual berbasis MATLAB sebagai kontrol Mobile Microrobot yang menggunakan modul mikro kontroler ESP8266. Robot bergerak dengan menerima perintah dari sistem kontrol menggunakan koneksi nirkabel WiFi. Algoritma pencarian rute yang digunakan merupakan sifat dari kecerdasan kerumunan semut ant colony , yang meliputi: penemuan rute route discovery , pemeliharaan rute route maintenance . Hasil akhir dari penelitian ini adalah sistem kontrol visual telah di-implementasikan algoritma pencarian rute swarm intelligence dari sifat yang dimiliki ant colony.

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Complexity demanding to the researchers to make artificial intelligence. The focus of this study is about implementing swarm intelligence for routing algorithm on the visual servoing control system MATLAB based, to control mobile microrobot with ESP8266 micro controller module. The robot moves by receiving task from a control system using a WiFi wireless connection. Routing Algorithm used is the nature intelligence from ant colony, which include route discovery, route maintenance, The end result of this research is visual control system has been implemented with swarm intelligence routing algorithm from the nature of ant colony. "

"ABSTRAKProses fabrikasi Li4Ti5O12 (LTO) dilakukan dengan metode solid state yaitu dengan menggiling bahan baku kemudian hasil penggilingan tersebut disinter. Bahan baku yang digunakan dalam penelitian ini adalah LiOH, TiO2 A (ukuran partikel 37 nm) dan TiO2 R (ukuran partikel 264 nm). Campuran bahan baku yang digunakan adalah LiOH­-TiO2 A dan LiOH-TiO2 R dengan perbandingan LiOH:TiO2 4:5. Penggilingan dilakukan menggunakan vibrating high speed milling (VHSM) dengan kecepatan rotasi penggilingan 2000 RPM. Variasi waktu penggilingan yang digunakan adalah 30 menit, 60 menit dan 90 menit. Sampel yang telah digiling sebagian dikompaksi dengan tekanan 200 MPa untuk mendapatkan variasi sampel dalam bentuk serbuk dan tablet. Kedua jenis sampel tersebut kemudian disinter dengan temperatur 800o C selama 240 menit dan preheat pada 480o C. Pengaruh perbedaan ukuran partikel TiO2, waktu penggilingan dan proses kompaksi diamati. Sampel yang terbetuk diuji dengan Field Emission Scanning Electron Microscope (FESEM), Braunner-Emmet-Teller (BET), Particle Size Analysis (PSA) dan X-Ray Diffraction (XRD).

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ABSTRACTLi4Ti5O12 (LTO) was synthesized by solid state method with milling the starting material then sintering the milling product. LiOH, TiO2 A (particle size 37 nm) and TiO2 R (particle size 264 nm) are used as starting materials. There are two kind of mixture in this research, LiOH-TiO2 A and LiOH-TiO2 R with LiOH-TiO2 ratio 4:5. Milling of mixture has been done by vibrating high speed milling (VHSM) with rotation speed 2000 RPM. LiOH-TiO2 mixture milled in three different time (30 minute, 60 minute and 90 minute). Half part of milled sample are compacted by 200 MPa pressure to make a different sample condition, tablet and powder sampel. Two kind of sampel are sintered in 800o C for 240 minute and preheat at 480o C. Effect of TiO2 particle size, milling time and compaction process are investigated. Sample were obtained by Field Emission Scanning Electron Microscope (FESEM), Braunner-Emmet-Teller (BET), Particle Size Analysis (PSA) dan X-Ray Diffraction (XRD)."