MEDIA STATISTIKA
Published by Universitas Diponegoro
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Articles 120 Documents
KAJIAN ESTIMASI-M IRLS MENGGUNAKAN FUNGSI PEMBOBOT HUBER DAN BISQUARE TUKEY PADA DATA KETAHANAN PANGAN DI JAWA TENGAH

Pradewi, Elen Dwi, Sudarno, Sudarno

MEDIA STATISTIKA Vol 5, No 1 (2012): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Original Source | Check in Google Scholar | Full PDF (606.598 KB) | DOI: 10.14710/medstat.5.1.1-10

Abstract

Ordinary Least Squares (OLS) is one method of parameter estimation in regression analysis. However, the presence of outliers can cause estimation of regression coefficients obtained are not exact. Act of throwing away an outlier is not a wise move, because sometimes outliers provide significant information. Therefore, robust regression methods are needed to data contain outliers. This paper will use robust regression estimation method by M-estimation. This estimation use Iteratively Reweighted Least Squares (IRLS) method with weighting function by Huber and Tukey Bisquare. IRLS is applied to the case of food security in Central Java in 2007 that is influenced by the stock of rice, harvested area, average production, price of rice and the amount of consumption. The purpose of this writing is to compare goodness of M-estimation IRLS using Huber and Tukey Bisquare function in estimating the model parameters of food security in Central Java in 2007. Based on the research results can be concluded that the M-estimation by the Tukey Bisquare is better recommended than Huber function. This can be seen by value results of Mean Square Error and determination coefficient

ANALISIS CLUSTER PADA KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN PRODUKSI PALAWIJA

Safitri, Diah, Widiharih, Tatik, Wilandari, Yuciana, Saputra, Arsyil Hendra

MEDIA STATISTIKA Vol 5, No 1 (2012): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Original Source | Check in Google Scholar | Full PDF (213.891 KB) | DOI: 10.14710/medstat.5.1.11-16

Abstract

Production of palawija, namely maize, cassava, sweet potato, peanut, soybean, and green bean is an important food crop in Central Java. In this article, districts/cities in Central Java are grouped into three groups based on the production of palawija so as to know which group have high potential the production of maize, cassava, sweet potato, peanut, soybean or green bean by using k-means cluster analysis. Cluster 1 consists of District Cilacap, Wonosobo, Magelang, Karanganyar, Semarang, Temanggung, Kendal, and Batang that have a high potential in maize production. Cluster 2 consists of District Banyumas, Purbalingga, Banjarnegara, Kebumen, Purworejo, Boyolali, Klaten, Sukoharjo, Sragen, Blora, Rembang, Pati, Kudus, Jepara, Demak, Pekalongan, Pemalang, Tegal, Brebes, Magelang City, Surakarta City, Salatiga City, Semarang City, Pekalongan City, and Tegal City  that have a high potential in peanut production. Cluster 3 consist of District Wonogiri and Grobogan that have a high potential in soybean production, green bean production, cassava production, and sweet potato production

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 : MEDIA STATISTIKA

Show Abstract | Original Source | Check in Google Scholar | Full PDF (341.567 KB)

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 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 : MEDIA STATISTIKA

Show Abstract | Original Source | Check in Google Scholar | Full PDF (408.769 KB)

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

KARAKTERISTIK UMUR PRODUK PADA MODEL WEIBULL

Sudarno, Sudarno

MEDIA STATISTIKA Vol 2, No 2 (2009): Media Statistika
Publisher : MEDIA STATISTIKA

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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.

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 : MEDIA STATISTIKA

Show Abstract | Original Source | Check in Google Scholar | Full PDF (430.172 KB)

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

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 : MEDIA STATISTIKA

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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.

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 : MEDIA STATISTIKA

Show Abstract | Original Source | Check in Google Scholar | Full PDF (240.488 KB)

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

IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN

Mukid, Moch. Abdul, Sugito, Sugito

MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Original Source | Check in Google Scholar | Full PDF (720.959 KB) | DOI: 10.14710/medstat.4.1.1-10

Abstract

This paper studies the implementation of Markov Chain Monte Carlo on estimating the hyperparameter of Gaussian process. Metropolish-Hasting (MH) algorithm is used to generate the random samples from the posterior distribution that can not be generated by a direct simulation method. This algorithm require only a proposal distribution for generating a candidate point. In this paper uniform distribution is choosen as the proposal distribution.   Keywords: Markov Chain Monte Carlo, Gaussian Process, Metropolis-Hasting Algorithm

PENGKONSTRUKSIAN KURVA YIELD DENGAN METODE NELSON SIEGEL SVENSSON (Studi Kasus Data Obligasi Pemerintah)

Setyawati, Winda, Hoyi, Abdul

MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Jurusan Statistika FSM Undip

Show Abstract | Original Source | Check in Google Scholar | Full PDF (598.515 KB) | DOI: 10.14710/medstat.4.1.13-22

Abstract

Bond is one of fixed-income investment instruments because of their income granted a return for investor based on the interest rates predetermined. The level of cash that returns to the investors and factor which must be considered by investor before invest bond is called yield. The term stucture of interest rates gives the relationship between the yield on an investment and the time to maturity of the investment. The graphic depiction of the relationship between the yield on bonds in the different maturities is known as the yield curve. The yield curve contruction of the government bond with bond ID is FR (Fixed Rate) by Nelson Siegel Svensson models on the trade date 16 on February 2011. The data is obtained from Indonesian Stock Exchange (IDX). The parameter estimation is done by ordinary least square. The optimation function for its estimation is done by Nelder Mead simplex. Yield curve on day 16 depicted upward sloping.   Keywords : Government Bond, Yield Curve, Fixed Rate, Nelson Siegel Svensson, Nelder Mead Simplex

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