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Yeni Kustiyahningsih
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Informatics Department, Engineering Faculty University of Trunojoyo Madura Jl. Raya Telang - Kamal, Bangkalan 69162, Indonesia Tel: 031-3012391, Fax: 031-3012391
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Jurnal Ilmiah Kursor
Published by Universitas Trunojoyo Madura
ISSN : 02160544     EISSN : 23016914     DOI : https://doi.org/10.21107/kursor
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Ilmiah Kursor is published in January 2005 and has been accreditated by the Directorate General of Higher Education in 2010, 2014, 2019, and until now. Jurnal Ilmiah Kursor seeks to publish original scholarly articles related (but are not limited) to: Computer Science. Computational Intelligence. Information Science. Knowledge Management. Software Engineering. Publisher: Informatics Department, Engineering Faculty, University of Trunojoyo Madura
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
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Search results for , issue "Vol 7 No 3 (2014)" : 6 Documents clear
PARTICLE SWARM OPTIMIZATION FOR MANAGING AS INJECTION ALLOCATION Hannan Fatoni; Mauridhi Hery P; Ardyono Priyadi
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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PARTICLE SWARM OPTIMIZATION FOR MANAGING AS INJECTION ALLOCATION aHannan Fatoni, bMauridhi Hery P, cArdyono Priyadi a Program Studi Magister ManajemenTeknologi, Institut Teknologi Sepuluh Nopember Jl. Cokroaminoto 12A, Surabaya, 60264, Indonesia b JurusanTeknikElektro, InstitutTeknologiSepuluhNopember Email: a hannanfatoni@gmail.com Abstract In oil and gas industry, the size of hydrocarbon reserves and type of the reservoir is crucial to the design methods and lifting the hydrocarbons for further processes. PT. XYZ uses the gas lift injection design to lift the oil content from the reservoir. In some conditions, the production choke valve shall be opened moreto increase the hydrocarbon production rates. However, it causes the reservoir instability, decreasing the reservoir pressure, and reducing the oil production drastically.Therefore, optimization of allocating gas lift injection rate on each of the production is needed to produce maximum oil and to improve the sustainability of oil and gas production on PT.XYZ. This paper proposes optimization technique for managing gas injection allocation using Particle Swarm Optimization (PSO). The procedure optimization can be explained as below; first step uses prosper modeling software to generate the model of production wells. Second, it obtains the curve of the gas lift injection rate against the oil production. Third, each well production model is validated by reference data from the well test result. The best PSO simulationwith limited gas injections which is 17 MMscfdresults of the gas lift injection allocation for each production wells are 0.98, 2.66, 1.39, 0.98, 3.19, 1.61, 1.78, 2.03, 1.40, and 0.98 MMscfd.With these gas injection allocations, the oil production increases to 4908.7 Barrels of oil per day (BPD). Maximum company profit after optimization reaching USD$ 578,004 compare with before optimization. The other optimization using Genetic Algorithm (GA) is also used for comparison. Keywords: Optimization, Prosper Modeling, PSO, GA.
DESIGN OPTIMIZATION OF MICRO HYDRO TURBINE USING ARTIFICIAL PARTICLE SWARM OPTIMIZATION AND ARTIFICIAL NEURAL NETWORK Lie Jasa; Ratna Ika Putri; Ardyono Priyadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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DESIGN OPTIMIZATION OF MICRO HYDRO TURBINE USING ARTIFICIAL PARTICLE SWARM OPTIMIZATION AND ARTIFICIAL NEURAL NETWORK aLie Jasa, bRatna Ika Putri, cArdyono Priyadi, dMauridhi Hery Purnomo a,b,c,d Instrumentation, Measurement, and Power Systems Identification Laboratory Electrical Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia a Electrical Engineering Department, Udayana University, Bali, Indonesia b Electrical Engineering Department, Politeknik Negeri Malang, Malang, Indonesia. Email: liejasa@unud.ac.id Abstrak Turbin digunakan mengkonversi energy potensial menjadi energy kinetik. Kapasitas Energy yang dihasilkan dipengaruhi oleh sudu-sudu turbin yang dipasang pada tepi. Sudu turbin dirancang seorang ahli dengan sudut kelengkungan tertentu. Efisiensi dari turbin dipengaruhi oleh besarnya sudut, jumlah dan bentuk sudu. Algoritma PSO dapat digunakan untuk komputasi dan optimasi dari design turbin mikro hidro. Penelitian ini dilakukan dengan; Pertama, Formula design turbin dioptimasi dengan PSO. Kedua, Data hasil optimasi PSO diinputkan kedalam jaringan ANN. Ketiga, training dan testing terhadap simulasi jaringan ANN. Dan yang terakhir, Analisa kesalahanr dari jaringan ANN. Data PSO sebanyak 180 record, 144 digunakan untuk training dan sisanya 40 untuk testing. Hasil penelitian ini adalah MAE= 0.4237, MSE=0.3826, dan SSE=165.2654. Error training terendah didapatkan dengan algoritma pembelajaran trainlm. Kondisi ini membuktikan bahwa jaringan ANN mampu menghasilkan desain turbin yang optimal. Kata kunci: Turbin, PSO, ANN, Energi Abstract Turbines are used to convert potential energy into kinetic energy. The blades installed on the turbine edge influence the amount of energy generated. Turbine blades are designed expertly with specific curvature angles. The number, shape, and angle of the blades influence the turbine efficiency. The particle swarm optimization (PSO) algorithm can be used to design and optimize micro-hydro turbines. In this study, we first optimized the formula for turbine using PSO. Second, we input the PSO optimization data into an artificial neural network (ANN). Third, we performed ANN network simulation testing and training. Finally, we conducted ANN network error analysis. From the 180 PSO data records, 144 were used for training, and the remaining 40 were used for testing. The results of this study are as follows: MAE = 0.4237, MSE = 0.3826, and SSE = 165.2654. The lowest training error was achieved when using the trainlm learning algorithm. The results prove that the ANN network can be used for optimizing turbine designs. Keywords: Turbine, PSO, ANN, Energy
MEASURING USER EXPERIENCE IN AN ONLINE STORE USING PULSE AND HEART METRICS Paulus Insap Santosa
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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MEASURING USER EXPERIENCE IN AN ONLINE STORE USING PULSE AND HEART METRICS Paulus Insap Santosa Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada Email: insap@ugm.ac.id Abstrak Beberapa sukses faktor toko daring dapat diringkas ke dalam elemen kebergunaan toko daring tersebut. Secara umum, kebergunaan berfokus pada kegunaan dan dapat digunakanya toko daring untuk membantu kustomer belanja secara daring. Akhir-akhir ini pengalaman positif pengguna ketika berbelanja secara daring menjadi tuntutan yang semakin nyata. Kebergunaan dan pengalaman pengguna adalah dua hal yang berbeda meskipun sangat berkaitan. Kebergunaan berfokus pada produk, dan pengalaman pengguna berfokus pada perasan dan emosi pengguna. Artikel ini melaporkan studi empiris untuk mengidentifikasi faktor yang berkontribusi pada pengalaman positif situs belanja daring. Responden berjumlah 121 yang merupakan mahasiswa yang belum pernah melakukan belanja daring. Para responden dihadapkan pada sebuah toko daring yang menjual beberapa barang. Mereka mengikuti skenario yang memungkinkan mereka melihat hampir semua fitur toko daring. Pengalaman pengguna diukur dengan menggunakan kombinasi metrik PULSE dan HEART dengan beberapa modifikasi untuk disesuaikan dengan keadaan. Analisis data menunjukkan bahwa responden mendapatkan manfaat yang lebih tinggi dibanding biaya yang harus ditanggung, dan kebahaguiaan dan sukses menjalankan tugas merupakan dua peubah yang memberikan pengaruh tertinggi kepada pengalaman pengguna. Kata kunci:pengalaman pengguna, kebergunaan, toko daring, PULSE, HEART, scenario Abstract Several success factors of online store can be summarized as usability. In general, usability focuses on how useful and usable the online store toward helping customers in doing their online shopping. Recently, more demand towards user positive experience becomes apparent. Usability and user experience are two different things but closely related. Usability focuses on products, and user experience focuses on user’s feelings and emotion. This paper reports an empirical study to determine factors contribute to positive experience in an online store success. There were 121 respondents who were students who had never done online shopping. They were exposed to a mockup online store selling several merchandises. They followed certain scenario that allowed them experiencing most online store features. User experience was measured using a combination of PULSE and HEART metrics with some modification to suit the current condition. Data analysis showed that respondents gained more benefit compared to the incurred cost, and happiness and task success were two variables provided more influence to user experience. Keywords: user experience, usability, online store, PULSE, HEART, scenario.
IMPROVED SIMULATED ANNEALING FOR OPTIMIZATION OF VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) Wayan Firdaus Mahmudy
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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IMPROVED SIMULATED ANNEALING FOR OPTIMIZATION OF VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW) Wayan Firdaus Mahmudy Department of Computer Science, University of Brawijaya (UB) Email: wayanfm@ub.ac.id Abstrak Vehicle routing proble with time windows (VRPTW) merupakan permasalahan optimasi kombinatorial yang banyak ditemui pada sistem distribusi permasalahan ini berkaitan dengan pengalokasian sejumlah kendaraan umum untuk melayani sejumlah konsumen, sejumlah konsumen mempunyai rentang waktu kesediaan yang berbeda dan harus dilayani dalam waktu tersebut. Paper ini memaparkan penggunaan metode simulated annealing yang diperkaya dengan beberapa fungsi khusus untuk menghasilkan solusi tetangga yang digunakan pada penelusuran are pencarian solusi dari VRPTW. Serangkaian percobaan menunjukkan bahwa simulated annealing yang diperkaya dengan fungsi-fungsi khusus dapat menghasilkan solusi yang baik dalam waktu rata-rata 82.29 detik. Kata kunci: Vehicle Routing Problem with Time Windows (VRPTW), Permasalahan optimasi kombinatoria, Simulated annealing, solusi tetangga. Abstract The Vehicle Routing Problem with Time Windows (VRPTW) is a combinatorial optimization problem that exists in various distribution systems. The problem deals with allocation of vehicles to service several customers, each customer has different available time, and the vehicles must visit the customers in their available time.This paper addresses the VRPTW by using an improved simulated annealing algorithm. Special functions to effectively exploring neighborhood solutions are developed. The functions are required to deal with the large search space of the VRPTW and enhance the power of the simulated annealing to obtain better solutions. The proposed approach is evaluated in comparison with well-known benchmark problems available in the literature. A set of computational experiments prove that the improved simulated annealing could produce promising results in the average of computational time of 82.29 seconds. Keywords: Vehicle Routing Problem with Time Windows (VRPTW), combinatorial optimization problem, simulated annealing, neighborhood solution
ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS Joko Pitono; Adi Soepriyanto; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS a Joko Pitono, bAdi Soepriyanto, cMauridhi Hery Purnomo aDepartment of Electrical Engineering, PPPPTK/VEDC Malang b,cDepartment of Electrical Engineering, Sepuluh Nopember Institute of Technology, Surabaya Email: j_pitono@yahoo.com Abstract The classical economic dispatch problem could be solved based on single objective function of power system operation by minimizing the fuel cost. However, the single objective function is not sustainable because the environmental issues arise from the emissions generated by fossil-fueled thermal electric power plants. Various pollutants such as sulfur dioxide (SO2), nitrogen oxides (NOX) and carbon dioxide (CO2) affect environmental issues. The economy-environment dispatch problem has been generally solved by considering each objective separately or by applying Weighted Sum Method on both objectives. This paper formulates the solution of dispatch PSO method that considers the impact of various pollutants and various factors such as the price penalty Min-Max, MaxMax, and Average in solving multi-objective problems using cubic criterion function for the cost of fuel and emission values. Multi-objective functions method proposed in this research was validated using IEEE 30-bus systems with six generating units. The results of simulation using Min-Max penalty factor indicated less total fuel cost value compared to the simulation using Max-Max and Average penalty factor. In general, the comparison of Min-Max type= 100%, Max-Max type= 266.9%, and Average type= 191.8%; Max-Max penalty factor provided less emission value with comparison to Min-Max and Average penalty factors. In general, the comparison Max-Max type= 100%, Min-Max type= 102%, and Average type= 100.2% to ETSO while for ETNO and ETCO is not significantly different; Average penalty factor provided less fuel cost value compared to Max-Max and Average penalty factor. In general, the comparison of Average type= 100%, Min-Max type= 101.8%, and Max-Max type= 100.3%. Keywords: Economic-Emission Dispatch, Multi-Objective, Cubic Criterion Function, Price Penalty Factors, Particle Swarm Optimization.
DESIGN OF GOAL-SEEKING BEHAVIOR-BASED MOBILE ROBOT USING PARTICLE SWARM FUZZY CONTROLLER Andi Adriansyah; Badaruddin .; Eko Ihsanto
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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DESIGN OF GOAL-SEEKING BEHAVIOR-BASED MOBILE ROBOT USING PARTICLE SWARM FUZZY CONTROLLER aAndi Adriansyah, bBadaruddin, cEko Ihsanto a,b,c Electrical Engineering Departement, Faculty of Engineering, Universitas Mercu Buana Jl. Meruya Selatan, Kembangan, Jakarta Barat, 11650, Indonesia Email: a andi@mercubuana.ac.id Abstract Behavior-based control architecture has successfully demonstrated their competence in mobile robot development. There is a key issue in behavior-based mobile robot namely the behavior design problems. Fuzzy logic system characteristics are suitable to address the problems. However, there are difficulties encountered when setting fuzzy parameters manually. Therefore, most of the works in the field generate certain interest for the study of fuzzy systems with added learning capabilities. This paper presents the development of fuzzy behavior-based control architecture using Particle Swarm Optimization (PSO). Then, goal-seeking behaviors based on Particle Swarm Fuzzy Controller (PSFC) are developed using the modified PSO with two stages of the PSFC process. A new nonlinear function of modulated inertia weight adaptation with time, named as Sigmoid Decreasing Inertia Weight (SDIW), is designed for improving the performance of PSO. Several simulations and experiments with MagellanPro mobile robot have been performed to analyze the performance of the algorithm. The promising results have proved that the proposed control architecture for mobile robot has better capability to accomplish useful task in real office-like environment. Keywords: behavior-based robot; fuzzy logic; PSO; PSFC

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