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ISSN : - EISSN : 24770647 DOI : -

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Decision Sciences, Operations Research & Management

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Articles 271 Documents

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PENENTUAN SEBARAN SPASIAL PENCEMARAN AIR DI KOTA PONTIANAK MENGGUNAKAN ANALISIS DISKRIMINAN DUA KELOMPOK Muhammad Fikri; Naomi Nessyana Debataraja; Dadan Kusnandar
MEDIA STATISTIKA Vol 12, No 2 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Clean water is one point of sustainable Development Goals (SDGs), so to keep indicator water quality must be determine every period. The Discriminant analysis is an analysis of dependence that is used to classify objects into several categories. The purpose of this study were to determine the discriminant model that consist of dominant factors of water pollution. Samples were taken from 42 locations in the surrounding area of Pontianak City. The sample were analyzed in the laboratory for the contents of ferrum (Fe), dissolved oxygen (DO), biochemical oxygen demand (BOD). Width of the river were also considered is an independent variable. The methodology includes determining the pollution index that will be used as dependent variable, testing the assumption of multivariate normality and similarity of the covariance variance, conducting the discriminant analysis classification process using the Apparent Error Rate method. The pollution level of each location was visualized in a map. The resulting discriminant model has an accuracy rate of 69%.

PEMETAAN PENYAKIT DEMAM BERDARAH DENGUE DENGAN ANALISIS POLA SPASIAL DI KABUPATEN PEKALONGAN Yasin, Hasbi; Saputra, Ragil
MEDIA STATISTIKA Vol 6, No 1 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The number of dengue haemorrhagic fever (DHF) incidence in Pekalongan from year to year is very volatile. In 2006, there was 352 cases, 718 cases occurred in 2007, 2008 saw 403 cases, 2009 there were 753 cases, whereas in 2010 a decline to 223 cases. This is possible due to the lack of information about the place, time and location of the incident spread of dengue in Pekalongan. Various efforts have been made to address these issues both society and government but the incidence of this disease has not been effectively suppressed. The results of data analysis showed that the incidence of dengue in Pekalongan mostly occurs during the rainy season is the period from January to June. The DHF incidence tends to be higher in Kedungwuni. Highest incidence of DHF occurred in April 2010. In addition, there are some months that indicate the spatial relationships in the incidence of dengue in Pekalongan, ie January, February, July, October and December. The sub-district that has a positive autocorrelation isÂ Kedungwuni, Wonopringgo, and Tirto. While the sub-district has a negative autocorrelation is Karangdadap. Most of the sub-districts in Pekalongan status is still endemic for dengue. Â Keywords: DHF, Moranâ€™s Index, Spatial Pattern

OPTIMISASI MULTIOBJEKTIF UNTUK PEMBENTUKAN PORTOFOLIO Hoyyi, Abdul; Ispriyanti, Dwi
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investing in asset such as stock; besides generate profit (return), it is also deal with a risk of loss, so that portofolio diversification is needed to reduce the risk. In the establishment of stock portofolio, the investors seeking to maximize the expected return of investment with a certain level of risk that still can be accepted. Portofolios that can achieve the above objectives called optimal portofolios. The application of multiobjective optimization on the establishment of the optimal portofolio is to maximize the return and minimize the risk at the same time. The aim of this research is to analize the proportion of each stock in order to form an optimal portofolio and to analyze the level of benefits and risks of the portofolio which is formed in accordance with the preferences of investors. The data used are monthly stock data of ASII, TLKM, SMGR, LPKR and BBNI. The optimal portofolio for risk seeker investors is a portofolio that used coefficient Â k =0,01, namely by investing in SMGR whilst the optimal portofolio for risk indifference investors is a portfolia which has coefficient 1 â‰¤ k â‰¤ 100 namely by investing in ASII, TLKM, SMGR, LPKR, and BBNI. Whereas, the optimal portofolio for risk averse investors is a portfolio which has coefficient k =1000 that is by investing in ASII, TLKM, SMGR, LPKR, and BBNI.Â Keywords: Portofolio, Multi Objective Optimization

PEMETAAN TINDAK KRIMINAL DI WILAYAH MADIUN DENGAN ANALISIS KORESPONDENSI BERGANDA Anindia Nufitasari; Hari Wijayanto; Itasia Dina Sulvianti
MEDIA STATISTIKA Vol 10, No 2 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multiple correspondence analysis is one of the statistical methods that can be used to describe the characteristics of criminal acts. Information about charateristic of crime is necessary to reduce the number of criminal acts. The purpose of this study is to describe criminal acts in the City and District of Madiun. Data sourced from Madiun City Police Station and Madiun District Police recording during 2016. The result of the research shows that criminal acts of theft, mistreatment and fraud have similar events characteristic at public place and residential area of Madiun City and Sub Unit of Development Area 2 at 06.00-11.59. Gambling and rape also characterize similar events at the crime scene residential area Sub Unit of Development Area 3 at 18.00-23.59. Illegal logging has different characteristics than other criminal acts. Meanwhile, theft, torture, and rape have characteristics of ≤ 25 years old and education level ≥ Senior High School (SHS). But criminal acts of fraud, illegal logging, and gambling have different characteristics of the perpetrators.

PENGUKURAN RISIKO PADA RETENSI OPTIMAL UNTUK REASURANSI STOP LOSS DENGAN VALUE AT RISK Sunarwatiningsih, Agustina; Wilandari, Yuciana; Rusgiyono, Agus
MEDIA STATISTIKA Vol 4, No 1 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Reinsurance is an effective risk management tool for an insurer to minimize the risk of loss. Optimization criteria is based in a minimum VaR of the total risk of in insurer, to derive the optimal retention in stop loss reinsurance. The resulting optimal solution of optimization criterion has several important characteristics, such as: the optimal retention has a very simple analytic form; the optimal retention depends only on the assumed loss distribution and the reinsurerâ€™s loading factor; if optimal solution exist, then VaR based optimization criteria yield the same optimal retentions; there exist a exceeds risk tolerance level which the insurer optimally should not reinsure her risks. The approach allows usÂ to obtain different results of the optimization problem depends on the measurement of risk used. Furthermore, with optimal retention of risk measurement and minimum of VaR to the total risk, the companies be able to minimize or reduce the loss ratio of claims own retention ceding company. One way to show the existence of an optimal retention used survival function distribution exponensial. Â Key words: Stop Loss Reinsurance, Optimal Retention, Value at Risk (VaR)

PERBANDINGAN MODEL CAPITAL ASSET PRICING MODEL (CAPM) DAN LIQUIDITY ADJUSTED CAPITAL ASSET PRICING MODEL (LCAPM) DALAM PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM SYARIAH Veladita Apriyanti; Epha Diana Supandi
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In stock investments, every investor wants to get a high level of return and low risk. The stock price is very volatile and unpredictable, this makes investors have to find solutions in order to get a benefit from this investment. One way is to form a portfolio. A portfolio is a collection of several shares. There are several models for calculating stock portfolios such as CAPM (Capital Asset Pricing Model) and LCAPM (Liquidity Adjusted Capital Asset Pricing Model). The CAPM is a model that describes the relationship between the expected return and risk of investing in a security. The LCAPM is an extension of CAPM by taking into account the liquidity of assets. Data from Jakarta Islamic Index is used to verify the two models. In this case, the empirical results show that the performance of CAPM is better than the LCAPM.

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI INDEK MUTU BENANG MENGGUNAKAN METODE POHON REGRESI (Studi Kasus di PT. Industri Sandang Nusantara Unit Patal Grati) Dewi, Hesti Sari; Wilandari, Yuciana; Sudarno, Sudarno
MEDIA STATISTIKA Vol 5, No 2 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Quality for ripe material (yarn) really necessary for the company, therefore needs to control the product (ripe material), so we are able to know the unmatched product percentage of the company standard and to know the cause of the unmatched. The appropriate method to know the influential factor to company yarn quality successes, among those regression tree method. Regression tree is one of CARTâ€™s classification method. CART is a useful non parametric statistical method to get an accurate data group as distinguishing as of a classification. Because it has continuous type of response variable, so that CART can create regression tree. Regression tree is utilized to figure relationship among one response variable with one or more predictor variable that gets continued character and also category. The variables that have influence for yarn quality index at PT. Industri Sandang Nusantara Patal Gratiâ€™s Unit are raw material, machine output year, air humidity (RH) and hall temperature. The result of the research is that the year of machine output variable is the most influence to foot up yarn quality index and has main contribution in the formation of regression tree. Â Keywords : Regression tree, CART, Yarn quality index, Rayon.

Perbandingan Sensitivitas Harga Obligasi Berdasarkan Durasi Macaulay dan Durasi Eksponensial dengan Pengaruh Konveksitas (Studi Empiris pada Data Obligasi Korporasi Indonesia yang Terbit Tahun 2015) Maruddani, Di Asih I; Hoyyi, Abdul
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Macaulay duration has often been used as a measure of the bond prices sensitivity to changes in interest rates. For a small change in interest rates, the duration provides a good approximation of the actual change in price. As the change in interest rates gets larger, the duration approximation has larger errors. The convexity of bond prices change is often used as a way to improve the accuracy of the approximation. Several authors have pointed out that the natural logarithm of bond price is a better measure of percentage changes in bond prices as interest rates change. Based on this idea, this paper derives an accurate method of estimating percentage bond price changes in response to changes in interest rates, which is called exponential duration. This paper gives new estimation of bond prices using exponential duration with convexity approach. It will be shown that the new estimation bond prices is always more accurate than by Macaulay duration with convexity approach. For empirical study, it is used corporate bond data, which is published by Indonesian Bond Pricing Agency in 2015. The result support the theory that error value of Macaulay duration with convexity is more than the error value of exponential duration with convexity.Keywords:Bond Price, Convexity, Exponential Duration, Macaulay Duration, Modified Duration

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

If x is a predictor variable and y is a responseÂ variable of Â the regression model y = f (x)+ ÃŽ withÂ f is a regression function which not yet been known and ÃŽ 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, Â the value ofÂ threshold has Â the most important role to determine Â level of smoothing estimator. The small threshold give function estimation very no smoothly, whileÂ 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 Â 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 Â the result of data analysis, the optimal threshold with cross validation method is not uniq, but they give the Â uniq of wavelet thersholding regression estimation. Â Keywords : Nonparametric Regression, Wavelet Threshold Estimator, Cross Validation.

PREDIKSI CURAH HUJAN EKSTREM DI KOTA SEMARANG MENGGUNAKAN SPATIAL EXTREME VALUE DENGAN PENDEKATAN MAX STABLE PROCESS (MSP) Hasbi Yasin; Budi Warsito; Arief Rachman Hakim
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This research covers Spatial Extreme Value method application with Max-Stable Process (MSP) approach that will be used to analysis Extreme Rainfall in Semarang city. Extreme value sample are selected by Block Maxima methods, it will be estimated into Spatial Extreme Value form by including location factors. Then it transform to Frechet distribution because it has a heavy tail pattern. Max Stable Process (MSP) is an extension of the multivariate extreme value distribution into infinite dimension of the Extreme Value Theory. After the best model of extreme rainfall data in Semarang is obtained, then calculated the prediction of extreme rainfall with a certain time period. Predictions are calculated using a return level, predictions of extreme rainfall using the return period of the next two years, at the Semarang City Climatology Station predicted to be a maximum of 100.7539 mm. At the Tanjung Mas Rain Monitoring Station it is predicted that a maximum of 100.1052 mm, Ahmad Yani Rain Monitoring Station is predicted to be a maximum of 109.9379 mm. Maximum prediction of extreme rainfall can also be calculated for future t (time) periods.

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