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INDONESIA
Media Statistika
Published by Universitas Diponegoro
ISSN : -     EISSN : 24770647     DOI : -
Core Subject : Science,
Decision Sciences, Operations Research & Management
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 2, No 2 (2009): Media Statistika" : 6 Documents clear
PENGUKURAN VALUE AT RISK PADA ASET TUNGGAL DAN PORTOFOLIO DENGAN SIMULASI MONTE CARLO Maruddani, Di Asih I; Purbowati, Ari
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (277.501 KB) | DOI: 10.14710/medstat.2.2.93-104

Abstract

Value at Risk (VaR) is the established standard for measuring market risk. VaR measures the worst expected loss under normal market conditions over a specific time interval at a given confidence level. A VaR statistic has three components: a time period, a confidence level and a loss amount (or loss percentage). The Monte Carlo simulation method calculates the change in the value of positions by using a random sample generated by price scenarios. Instead of using the past value of risk factors, Monte Carlo simulation generates models to estimate the risk factors from past portfolio returns by specifying the distributions and their parameters. Using these distributions and parameters, we can generate thousands of hypothetical scenarios for risk factors and, finally, we can determine future prices or rates based on hypothetical scenarios. VaRs can be derived from the cumulative distribution of future prices or rates for given confidence levels. In this paper, we calculate VaR at PT Astra International Tbk., PT Telekomunikasi Tbk., and the portfolio of the two assets. PT. Astra International Tbk has higher VaR than PT. Telekomunikasi Tbk. The VaR of a portfolio has lower result than VaR of each single asset.   Keywords : Value at Risk, Time Period, Confidence Level, Monte  Carlo Simulation.
KARAKTERISTIK UMUR PRODUK PADA MODEL WEIBULL Sudarno, Sudarno
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (179.855 KB) | DOI: 10.14710/medstat.2.2.105-110

Abstract

Long life of product can reflect its quality. Generally, good products have long life. There are functions that relationship with life as reliability function, hazard rate function, mean time to failure, and mean residual life. In this writing those functions be used to product which has the failure time of a component is distributed Weibull. The reliability function is exponential function. For value θ is constant, the reliability value is decrease function, if γ is greather with respect to time. Meanwhile hazard rate function could be monotone increase function, constant function, monotone decrease function, if doing by simulation with shape parameter by one. Really, the mean time to failure product hang on Weibull distribution parameters. But the mean residual life is reciprocal with respect to its reliability.   Keywords:      Weibull Model, Reliability and Hazard Rate Functions, Mean Time to Failure, Mean Residual Life.
PEMILIHAN THRESHOLD OPTIMAL PADA ESTIMATOR REGRESI WAVELET THRESHOLDING DENGAN METODE CROSS VALIDASI Suparti, Suparti; Tarno, Tarno; Hapsari, Paula Meilina Dwi
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.567 KB) | DOI: 10.14710/medstat.2.2.56-69

Abstract

If x is a predictor variable and y is a response  variable of  the regression model y = f (x)+ Î with  f is a regression function which not yet been known and Î is independent random variable with mean 0 and variance , hence function f can be estimated by parametric and nonparametric approach. In this paper function f is estimated with a nonparametric approach. Nonparametric approach that used is a wavelet shrinkage or a wavelet threshold method. In the function estimation with a wavelet threshold method,  the value of  threshold has  the most important role to determine  level of smoothing estimator. The small threshold give function estimation very no smoothly, while  the big value of threshold give function estimation very smoothly. Therefore the optimal value of threshold should be selected to determine the optimal function estimation. One of the methods to determine the optimal value of threshold by minimize a cross validation function. The cross validation method that be used is two-fold cross validatiaon. In this cross validation, it compute the predicted value by using a half of data set. The original data set is split  into two subsets of equal size : one containing only the even indexed data, and the other, the odd indexed data. The odd data will be used to predict the even data, and vice versa. Based on  the result of data analysis, the optimal threshold with cross validation method is not uniq, but they give the  uniq of wavelet thersholding regression estimation.   Keywords : Nonparametric Regression, Wavelet Threshold Estimator, Cross Validation.
ANALISIS SISTEM ANTRIAN KERETA API DI STASIUN BESAR CIREBON DAN STASIUN CIREBON PRUJAKAN Sugito, Sugito; Fauzia, Marissa
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (240.488 KB) | DOI: 10.14710/medstat.2.2.111-120

Abstract

Queue system is a group of customer, service, and some rules to regulate arrival customers. Queue happened if a customers which need a serve more than service capacity. Phenomenon queue will find easily in public facility. One of is train  queue at Cirebon Main Train Station  and Cirebon Prujakan Train Station. Queue happened from train awaiting to be ridden away and from train which would to go to station, so that makes sometimes inappropriate arrival and departure the train of schedule resulting cumulative of train passenger candidate. To analyse  problems of train queue happened in station Cirebon can be applied the application of the queue theory. The steps must to do is by to create the examination where the queue happened. Based on those analysis can be known queue model and performance measure of queue system. And from data analysis can get two best kind of model for service system at Cirebon Main Train Station, that is (M/M/1):(GD/∞/∞) and (G/G/3):(GD/∞/∞). And two model service system at Cirebon Prujakan Train station, that is (M/G/2):(GD/∞/∞) and (M/G/1):(GD/∞/∞).   Keywords : Queue System, The Cirebon Station, Queue Model
ANALISIS DATA PANEL UNTUK MENGUJI PENGARUH RISIKO TERHADAP RETURN SAHAM SEKTOR FARMASI DENGAN LEAST SQUARE DUMMY VARIABLE Astuti, Tutut Dewi; Maruddani, Di Asih I
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.769 KB) | DOI: 10.14710/medstat.2.2.71-80

Abstract

Panel data analysis is a method of studying pooling observations on a cross-section of subjects over several time periods. There are several types of panel data analytic models, constant coefficients models, fixed effects models, and random effects models. Fixed effects models would have constant slopes but intercepts that differ according to the cross-sectional (group) unit. While the intercept is cross-section (group) specific, it may or may not differ over time. To show how to test for the presence of statistically significant group and/or time effects, i-1 dummy variables are used to designate the particular group, so we use Least Squares Dummy Variable method. In this paper, we use this method for testing the relationship between risk and stock return at farmation sector data in Indonesia for the time period 2007-2008. The empirical results showed that the model is statistically significant time effects.   Keywords : Risk, Stock Return, Panel Data, Least Square Dummy Variable
METODE TAGUCHI UNTUK OPTIMALISASI PRODUK PADA RANCANGAN FAKTORIAL Wuryandari, Triastuti; Widiharih, Tatik; Anggraini, Sayekti Dewi
MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (430.172 KB) | DOI: 10.14710/medstat.2.2.81-92

Abstract

Taguchi methods represent the effort quality improvement which known as off-line quality control  method because the method design quality into every appropriate process and product. Taguchi methods is represent quality repair with attempt “new” methods, its meaning do dissimilar approach giving same belief storey by SPC (Statistical Proces Control), very effective in quality improvement as well as lessening expense of same. Fractional factorial design represent base from Taguchi method by fraction from factorial design. Fractional factorial with  4 factors and defining relations p = 2 is or 81 run become or 9 blocks with each blocks there are 9 run just eligible one block. The block name that is Orthogonal Array which lessen time and attemp fare. Orthogonal Array used to device of factorial attemp 3 level by 4 factors that is Orthogonal Array L9. Optimalitation product of factorial design  can be determinate with tables of anova, table of response and tables of Signal to Noise Ratio.   Keywords: Taguchi Methods, Signal to Noise Ratio, Orthogonal Array

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