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All Journal International Journal of Electrical and Computer Engineering Jurnal Matematika & Sains Journal of Mathematical and Fundamental Sciences
Udjianna Sekteria Pasaribu
Statistics Research Division, Faculty of Mathematics and Natural Science, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia
Astronomy Chemistry Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Mathematics Physics

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Spektrum Gstar(1;1) Nunung Nurhayati; Udjianna Sekteria Pasaribu; Dudung Muhally Hakim; Oki Neswan
Jurnal Matematika & Sains Vol 13, No 4 (2008)
Publisher : Institut Teknologi Bandung

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Abstract

In this paper we formulate the spectrum (spectral density matrix) of the stationary GSTAR(1;1) model by considering the model as VMA( ∞). The spectrum can be obtained by following steps: represent the model as an VMA( ∞) and convert the model to the backward operator form, then substitute the coefficient model to the spectrum of VMA( ∞) model. The procedure of finding spectrum of GSTAR(1;1) which parameters are given, is illustrated by a two dimensional GSTAR(1;1) model.
Effective Router Assisted Congestion Control for SDN Sofia Naning Hertiana; Adit Kurniawan; Hendrawan Hendrawan; Udjianna Sekteria Pasaribu
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.805 KB) | DOI: 10.11591/ijece.v8i6.pp4467-4476

Abstract

Router Assisted Congestion Control (RACC) was designed to improve endto- end congestion control performance by using prior knowledge on network condition. However, the traditional Internet does not provide such information, which makes this approach is not feasible to deliver. Our paper addresses this network information deficiency issue by proposing a new congestion control method that works on the Software Defined Network (SDN) framework. We call this proposed method as PACEC (Path Associativity Centralized Congestion Control). In SDN, global view of the network information contains the network topology including link properties (i.e., type, capacity, power consumption, etc.). PACEC uses this information to determine the feedback signal, in order for the source to start sending data at a high rate and to quickly reach fair-share rate. The simulation shows that the efficiency and fairness of PACEC are better than Transmission Control Protocol (TCP) and Rate Control Protocol (RCP).
Error Assumptions on Generalized STAR Model Yundari Yundari; Udjianna Sekteria Pasaribu; Utriweni Mukhaiyar
Journal of Mathematical and Fundamental Sciences Vol. 49 No. 2 (2017)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2017.49.2.4

Abstract

For GSTAR models, the least squares estimation method is commonly used since errors are assumed be uncorrelated. However, this method is not appropriate when errors are correlated, either in time or spatially. For these cases, the generalized least squares (GLS) method can be applied. GLS is more powerful since it has an error parameter that can act as a controller of the model to produce an efficient estimator. In this study, R Software was used to estimate GSTAR parameters. The resulted model was applied to real data, i.e. the monthly tea production of five plantations in West Java, Indonesia. The best model for forecasting was the GSTAR(1;1) model with temporally correlated error assumption.
The Modified Double Sampling Coefficient of Variation Control Chart Fachrur Rozi; Udjianna Sekteria Pasaribu; Utriweni Mukhaiyar; Dradjad Irianto
Journal of Mathematical and Fundamental Sciences Vol. 55 No. 1 (2023)
Publisher : Directorate for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2023.55.1.4

Abstract

The concept of monitoring the coefficient of variation has gained significant interest in quality control, particularly in situations where the mean and standard deviation of a process are not constant. This study modified the procedure of the previous double sampling chart for monitoring the coefficient of variation, developed by Ng et al. in 2018. Instead of using only information from the second sample, here, information from both samples is used. The probability properties of the out-of-control signal and run length of this chart are presented. To evaluate the chart’s performance, the optimal design and a comparison with the previous double sampling control chart using average run-length criteria are described. It was found that the modified double sampling chart has better performance and is more efficient compared to the previous chart, especially when the total sample size is smaller. As a study case, the application of this chart is illustrated using real data from a molding process. This confirmed that the modified double sampling chart improved performance in detecting out-of-control signals. Thus, the modified chart is recommended to be applied in industry.
Co-Authors Adit Kurniawan Dradjad Irianto Dudung Muhally Hakim Fachrur Rozi Hendrawan Hendrawan Nunung Nurhayati Oki Neswan Sofia Naning Hertiana Utriweni Mukhaiyar Yundari, Yundari