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All Journal International Journal of Electrical and Computer Engineering Media Statistika MATEMATIKA Jurnal Ilmu Dasar Jurnal Natur Indonesia TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Journal of the Indonesian Mathematical Society International Journal of Advances in Intelligent Informatics PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Jurnal Ilmiah Matrik Jurnal Statistika dan Matematika (Statmat)
Subanar .
Department Of Mathematics, Universitas Gadjah Mada
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics Other

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Journal : International Journal of Advances in Intelligent Informatics

 1 
Forecasting electricity load demand using hybrid exponential smoothing-artificial neural network model Winita Sulandari; Subanar Subanar; Suhartono Suhartono; Herni Utami
International Journal of Advances in Intelligent Informatics Vol 2, No 3 (2016): November 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i3.69

Abstract

Short-term electricity load demand forecast is a vital requirements for power systems. This research considers the combination of exponential smoothing for double seasonal patterns and neural network model. The linear version of Holt-Winter method is extended to accommodate a second seasonal component. In this work, the Fourier with time varying coefficient is presented as a means of seasonal extraction. The methodological contribution of this paper is to demonstrate how these methods can be adapted to model the time series data with multiple seasonal pattern, correlated non stationary error and nonlinearity components together. The proposed hybrid model is started by implementing exponential smoothing state space model to obtain the level, trend, seasonal and irregular components and then use them as inputs of neural network. Forecasts of future values are then can be obtained by using the hybrid model. The forecast performance was characterized by root mean square error and mean absolute percentage error. The proposed hybrid model is applied to two real load series that are energy consumption in Bawen substation and in Java-Bali area. Comparing with other existing models, results show that the proposed hybrid model generate the most accurate forecast
Simulation of queue with cyclic service in signalized intersection system Muhammad Dermawan Mulyodiputro; Subanar Subanar
International Journal of Advances in Intelligent Informatics Vol 1, No 1 (2015): March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v1i1.15

Abstract

The simulation was implemented by modeling the queue with cyclic service in the signalized intersection system. The service policies used in this study were exhaustive and gated, the model was the M/M/1 queue, the arrival rate used was Poisson distribution and the services rate used was Exponential distribution. In the gated service policy, the server served only vehicles that came before the green signal appears at an intersection. Considered that there were 2 types of exhaustive policy in the signalized intersection system, namely normal exhaustive (vehicles only served during the green signal was still active), and exhaustive (there was the green signal duration addition at the intersection, when the green signal duration at an intersection finished). The results of this queueing simulation program were to obtain characteristics and performance of the system, i.e. average number of vehicles and waiting time of vehicles in the intersection and in the system, as well as system utilities. Then from these values, it would be known which of the cyclic service policies (normal exhaustive, exhaustive and gated) was the most suitable when applied to a signalized intersection system
Estimating the function of oscillatory components in SSA-based forecasting model Winita Sulandari; Subanar Subanar; Suhartono Suhartono; Herni Utami; Muhammad Hisyam Lee
International Journal of Advances in Intelligent Informatics Vol 5, No 1 (2019): March 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v5i1.312

Abstract

The study of SSA-based forecasting model is always interesting due to its capability in modeling trend and multiple seasonal time series. The aim of this study is to propose an iterative ordinary least square (OLS) for estimating the oscillatory with time-varying amplitude model that usually found in SSA decomposition. We compare the results with those obtained by nonlinear least square based on Levenberg Marquardt (NLM) method. A simulation study based on the time series data which has a linear amplitude modulated sinusoid component is conducted to investigate the error of estimated parameters of the model obtained by the proposed method. A real data series was also considered for the application example. The results show that in terms of forecasting accuracy, the SSA-based model where the oscillatory components are obtained by iterative OLS is nearly the same with that is obtained by the NLM method.
Co-Authors Abdurakhman . Abdurakhman . Abdurakhman Abdurakhman Agus Maman Abadi Bambang Widjanarko Otok Dedy Rosadi Endah Wulan Perwitasari, Endah Wulan Herni Utami Herni Utami Luh Putu Widya Adnyani Mayawi, Mayawi MHD. Reza M.I. Pulungan Muhammad Dermawan Mulyodiputro Muhammad Hisyam Lee Muhammad Hisyam Lee Paulo Canas Rodrigues Putriaji Hendikawati Rohmatul Fajriyah Samsubar Saleh Seng Hansun Sri Rezeki Suhartono . Suhartono Suhartono Suhartono Suhartono Suhartono Suhartono Sukono Sukono Suryo Guritno Suryo Guritno Tarno Tarno Tarno Tarno Vemmie Nastiti Lestari Widodo Widodo Winita Sulandari Winita Sulandari Winita Sulandari Wiwin Sulistyo Zanzawi S. Zanzawi S.