Dedy Dwi Prastyo
Fakultas Matematika dan Ilmu Pengetahuan Alam, Jurusan Statistika Institut Teknologi Sepuluh Nopember

Published : 8 Documents
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FUZZY MODELING APPROACH AND GLOBAL OPTIMIZATION FOR DUAL RESPONSE SURFACE

Jurnal Teknik Industri Vol 9, No 2 (2007): DECEMBER 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Original Source | Check in Google Scholar | Full PDF (220.088 KB)

Abstract

Dual Response Surface (DRS) with Lagrange multiplier is one of the most familiar classical multi response surface methods. Classical DRS optimization doesn´t concern about the quality characteristic of responses. In this paper, fuzzy approach is proposed for modeling DRS and quality characteristic of response simultaneously. The proposed method represented the object´s quality characteristic physically. The proposed method is applied to composite carbon drilling process and resulting nonlinear function that to be determined its optimal point. Many optimization methods fail to reach global optimum point because the non linear function is multimodal. Therefore, we used genetic algorithm for finding the global optimum point.

KINERJA ECONOMIZER PADA BOILER

Jurnal Teknik Industri Vol 11, No 1 (2009): JUNE 2009
Publisher : Institute of Research and Community Outreach - Petra Christian University

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Abstract

This paper employed the dual response approach for case of Multivariate Robust Parameter Design (MRPD) which is developed by Del Castillo and Miro Quesada. MRPD method can be applied for any design of experiment. The optimization in this method uses minimizing variance function with restriction on mean function. In this paper, MRPD is applied to the case of optimization of heat transfer efectivity and operational cost at economizer. Those two responses are optimized by setting the level of control factors; diametre of tube hole, transversal spacing, and fin nearness. Temperature of feedwater is hold as a noise factor. Optimization is calculated by fmincon in MATLAB 7.0. The optimal condition for heat tranfer efectivity is 77.17% and operational cost is 30.58 kW. The optimal condition is attained at diametre of tube hole 1.5 inch, transversal spacing 3.5 inch, and fin density 3 fin/inch. Abstract in Bahasa Indonesia: Penelitian ini menggunakan metode pendekatan dual response terhadap kasus Multivariate Robust Parameter Design (MRPD) yang dikembangkan oleh Del Castillo dan Miro Quesada. Metode MRPD tidak mensyaratkan jenis rancangan percobaan yang dapat digunakan dalam proses optimasi, yang dilakukan dengan meminimalkan fungsi varians terhadap kendala fungsi rerata. Pada penelitian ini, metode MRPD diterapkan untuk kasus pencarian nilai optimal respon yaitu efektifitas perpindahan panas dan biaya operasi pada economizer. Optimasi kedua respon dilakukan dengan cara mengoptimalkan level faktor kontrol diameter luar tubing, transversal spacing, dan kerapatan fin. Temperatur feedwater berlaku sebagai faktor noise. Optimasi dilakukan dengan bantuan fmincon pada MATLAB 7.0 yang menghasilkan kondisi optimum untuk efektifitas perpindahan panas sebesar 77,17% dan biaya operasi sebesar 30,58 kW. Kondisi tersebut dicapai pada saat level diameter luar tubing sebesar 1,5 inci, transversal spacing sebesar 3,5 inci, dan kerapatan fin sebesar 3 fin/inci. Kata kunci: Economizer, dual response, Multivariate Robust Parameter Design

Regression Models for Spatial Data: An Example from Gross Domestic Regional Bruto in Province Central Java

Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Vol 18, No 2 (2017): JEP 2017
Publisher : Universitas Muhammdaiyah Surakarta

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Abstract

The important role of a regions transportation infrastructure strongly affects the economic growth of the region and tends to affect the surrounding areas. The effect is called spillover effect. The aim of the research was to recognize the direct effect and spillover effect (indirect) of transportation infrastructure on the economic growth in Central Java. To identify the spillover effects, it is necessary to recognize the different characteristics of each region which have the implications on the various transportation infrastructures at each region in Central Java. Therefore, the spatial modeling was conducted. In this study, the spatial modeling employed was Spatial Durbin Error Model (SDEM). The SDEM is another form of Spatial Error Model (SEM). It does not allow for lag effects of endogenous variables, but it allows for spatial error and spatial lag on exogenous variables in which it simplifies the interpretations on direct effects and spillover effect. According to SDEM estimates, the transportation infrastructures at the districts/municipalities in Central Java had no significant effect on the outputs at each region where the infrastructures were located and their neighboring districts/cities

FUZZY MODELING APPROACH AND GLOBAL OPTIMIZATION FOR DUAL RESPONSE SURFACE

Jurnal Teknik Industri Vol 9, No 2 (2007): DECEMBER 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Original Source | Check in Google Scholar | Full PDF (220.088 KB)

Abstract

Dual Response Surface (DRS) with Lagrange multiplier is one of the most familiar classical multi response surface methods. Classical DRS optimization doesnt concern about the quality characteristic of responses. In this paper, fuzzy approach is proposed for modeling DRS and quality characteristic of response simultaneously. The proposed method represented the objects quality characteristic physically. The proposed method is applied to composite carbon drilling process and resulting nonlinear function that to be determined its optimal point. Many optimization methods fail to reach global optimum point because the non linear function is multimodal. Therefore, we used genetic algorithm for finding the global optimum point.

KINERJA ECONOMIZER PADA BOILER

Jurnal Teknik Industri Vol 11, No 1 (2009): JUNE 2009
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Original Source | Check in Google Scholar | Full PDF (260.399 KB)

Abstract

This paper employed the dual response approach for case of Multivariate Robust Parameter Design (MRPD) which is developed by Del Castillo and Miro Quesada. MRPD method can be applied for any design of experiment. The optimization in this method uses minimizing variance function with restriction on mean function. In this paper, MRPD is applied to the case of optimization of heat transfer efectivity and operational cost at economizer. Those two responses are optimized by setting the level of control factors; diametre of tube hole, transversal spacing, and fin nearness. Temperature of feedwater is hold as a noise factor. Optimization is calculated by fmincon in MATLAB 7.0. The optimal condition for heat tranfer efectivity is 77.17% and operational cost is 30.58 kW. The optimal condition is attained at diametre of tube hole 1.5 inch, transversal spacing 3.5 inch, and fin density 3 fin/inch. Abstract in Bahasa Indonesia: Penelitian ini menggunakan metode pendekatan dual response terhadap kasus Multivariate Robust Parameter Design (MRPD) yang dikembangkan oleh Del Castillo dan Miro Quesada. Metode MRPD tidak mensyaratkan jenis rancangan percobaan yang dapat digunakan dalam proses optimasi, yang dilakukan dengan meminimalkan fungsi varians terhadap kendala fungsi rerata. Pada penelitian ini, metode MRPD diterapkan untuk kasus pencarian nilai optimal respon yaitu efektifitas perpindahan panas dan biaya operasi pada economizer. Optimasi kedua respon dilakukan dengan cara mengoptimalkan level faktor kontrol diameter luar tubing, transversal spacing, dan kerapatan fin. Temperatur feedwater berlaku sebagai faktor noise. Optimasi dilakukan dengan bantuan fmincon pada MATLAB 7.0 yang menghasilkan kondisi optimum untuk efektifitas perpindahan panas sebesar 77,17% dan biaya operasi sebesar 30,58 kW. Kondisi tersebut dicapai pada saat level diameter luar tubing sebesar 1,5 inci, transversal spacing sebesar 3,5 inci, dan kerapatan fin sebesar 3 fin/inci. Kata kunci: Economizer, dual response, Multivariate Robust Parameter Design

Hybrid SSA-TSR-ARIMA for water demand forecasting

International Journal of Advances in Intelligent Informatics Vol 4, No 3 (2018): November 2018
Publisher : Universitas Ahmad Dahlan

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Abstract

Water supply management effectively becomes challenging due to the human population and their needs have been growing rapidly. The aim of this research is to propose hybrid methods based on Singular Spectrum Analysis (SSA) decomposition, Time Series Regression (TSR), and Automatic Autoregressive Integrated Moving Average (ARIMA), known as hybrid SSA-TSR-ARIMA, for water demand forecasting. Monthly water demand data frequently contain trend and seasonal patterns. In this research, two groups of different hybrid methods were developed and proposed, i.e. hybrid methods for individual SSA components and for aggregate SSA components. TSR was used for modeling aggregate trend component and Automatic ARIMA for modeling aggregate seasonal and noise components separately. Firstly, simulation study was conducted for evaluating the performance of the proposed methods. Then, the best hybrid method was applied to real data sample. The simulation showed that hybrid SSA-TSR-ARIMA for aggregate components yielded more accurate forecast than other hybrid methods. Moreover, the comparison of forecast accuracy in real data also showed that hybrid SSA-TSR-ARIMA for aggregate components could improve the forecast accuracy of ARIMA model and yielded better forecast than other hybrid methods. In general, it could be concluded that the hybrid model tends to give more accurate forecast than the individual methods. Thus, this research in line with the third result of the M3 competition that stated the accuracy of hybrid method outperformed, on average, the individual methods being combined and did very well in comparison to other methods.

PENGUJIAN LAGRANGE MULTIPLIER PADA SPESIFIKASI SPATIAL MODEL PERTUMBUHAN EKONOMI INDONESIA

PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2018: SEMINAR NASIONAL PENDIDIKAN SAINS DAN TEKNOLOGI
Publisher : Universitas Muhammadiyah Semarang

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Abstract

Beberapa model ekonometrika didasari pada teknik asimtotik dan terdapat tiga prinsip untuk pembangunan tes hipotesis parametrik. Pengujian tersebut diantaranya : (i) metode Wald, (ii) metode maximum likelihood ratio (LR) dan (iii) metode Lagrange Multiplier (LM). Terdapat uji diagnostik untuk penilaian model yang disebabkan dependensi spatial dan heterogenitas spatial sebagai aplikasi dari prinsip Lagrange Multiplier. Tujuan dari paper ini adalah mempertimbangkan penggunaan uji Lagrange Multiplier untuk menyusun spesifikasi model spatial pertumbuhan ekonomi di Indonesia. Data yang digunakan  adalah  produk  domestic  regional  bruto  (PDRB)  untuk  masing- masing provinsi serta faktor-faktor yang mempengaruhinya bersumber dari Badan Pusat Statistik Republik Indonesia (BPS RI) tahun 2017. Berdasarkan hasil  pengujian  LM  mengindikasikan  bahwa  parameter  rho  dan  lamda (SARMA) berpengaruh signifikan. Dengan demikian, spesifikasi model spatial terbaik adalah model yang menambahkan parameter rho dan lamda, seperti model spatial SAC dan SAC mixed.Keywords:   Lagrange   Multiplier,   Uji   Diagnostik  Spatial,   Spatial   Model, pertumbuhan ekonomi, infrastruktur transportasi.

Pemilihan Arsitektur Terbaik pada Model Deep Learning Melalui Pendekatan Desain Eksperimen untuk Peramalan Deret Waktu Nonlinier

STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 18, No 2 (2018)
Publisher : Program Studi Statistika Unisba

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Abstract

Penentuan arsitektur model deep learning yang tepat merupakan hal yang sangat esensial untukmendapatkan hasil ramalan dengan tingkat kesalahan minimum. Arsitektur deep learning meliputijumlah input dan variabel apa saja yang digunakan, jumlah hidden layer, jumlah neuron pada setiaphidden layer, dan fungsi aktivasi. Pada penelitian ini dilakukan studi simulasi pada salah satu modeldeep learning, yaitu deep feedforward network, dengan berbagai kombinasi arsitektur untukmendapatkan arsitektur paling optimum. Data yang digunakan merupakan data bangkitan yangmengikuti model nonlinier Exponential Smoothing Transition Auto-regressive (ESTAR) sebanyak 1000data, di mana 900 data digunakan sebagai data training dan 100 data digunakan sebagai datatesting. Ukuran evaluasi model yang digunakan adalah root mean square error of prediction (RMSEP).Hasil empiris yang didapatkan di antaranya, pemilihan input yang tepat dapat meningkatkanakurasi peramalan, serta pemilihan fungsi aktivasi dan kedalaman arsitektur sangat diperlukanuntuk mendapatkan hasil ramalan yang semakin optimum.