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Tiananda Widyarini
Fakultas Teknologi Industri, Jurusan Teknik Industri, Institut Teknologi Sepuluh Nopember Surabaya
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering

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Aplikasi Metode Cross Entropy untuk Support Vector Machines Santosa, Budi; Widyarini, Tiananda
Jurnal Teknik Industri Vol 10, No 2 (2009): Agustus
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.883 KB) | DOI: 10.22219/JTIUMM.Vol10.No2.150-157

Abstract

Support vector machines (SVM) is a robust method for  classification problem. In the original formulation, the dual form of SVM must be solved by a quadratic programming in order to get the optimal solution. The shortcoming of the standard version is as the classification problem is getting larger, the high computing time is needed. Cross entropy (CE) is a newly discovered optimization method with two main procedures: generating data samples by a chosen distribution, and updating the distribution parameters due to elite samples to generate a better sample in the next iteration. The CE method has been applied in many optimization problems with satisfying result. In this research, CE is applied to solve the optimization problem of Lagrangian SVM for faster  computational time. This method is tested in some real world datasets for classification problem. The results show that the application of CE in SVM is comparable to standard SVM in classifying two class data in terms of accuracy. In addition, this method can solve large datasets classification problem faster than standard SVM.
Integrasi Produksi - Distribusi pada Supply Chain dengan Pendekatan Hybrid Analitik - Simulasi Garside, Annisa Kesy; Wahyuono, R. Hadi; Widyarini, Tiananda
Jurnal Teknik Industri Vol 13, No 1 (2011): JUNE 2011
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (251.969 KB) | DOI: 10.9744/jti.13.1.27-36

Abstract

Integrated production-distribution problem resolution using analytical model lacks of consideration of many uncertainties along supply chain line such as delays, queues, machine breakdown, vehicle malfunction, and environmental factor. By utilizing simulation as complex stochastic system modelling, this research aims to develop hybrid analytical-simulation approach to resolve integrated production-distribution model. Time capacity adjustment is required if production-distribution plan obtained from analytical model requires longer production and delivery time than available. The adjustment is using a procedure developed based on duration obtained from simulation model and is used to obtain adjusted time capacity. The implementation of hybrid method to resolve integrated production-distribution problem on two echelon supply chain with 2 factories and 5 DCs shows a feasible solution was obtained on the third iteration
Co-Authors Annisa Kesy Garside Budi Santosa R. Hadi Wahyuono