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Media Statistika

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ISSN : - EISSN : 24770647 DOI : -

Core Subject : Science,

Decision Sciences, Operations Research & Management

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Articles 271 Documents

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ANALISIS PENGARUH KARAKTERISTIK WILAYAH (KELURAHAN) TERHADAP BANYAKNYA KASUS DEMAM BERDARAH DENGUE (DBD) DI KOTA SEMARANG Rahmawati, Rita; Kartono, Kartono; Sulistyo, Robertus Heri; Noranita, Betha; Sarwoko, Eko Adi; Wardaya, Asep Yoyo
MEDIA STATISTIKA Vol 5, No 2 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

DBD still become one of the major problems of public health in Indonesia because the death rate tended sufferers to increase from year to year. Incredible happening (KLB) of DBD which was initially occurring every five years, now itâ€™s getting often happens. In the city of Semarang, during 2009 occurring 165 times KLB in urban village, 35 times KLB in the level of community health centers and 15 times KLB at the district level. Though the number of DBD cases in 2009 from 2008 was declining, but in this year also noted that the number of deaths resulting from DBD increased to 43 people from 18 people in 2008. This research aims to analyze the characteristics of the neighborhood (whose data is always updated by BPS via PODES) that affect the number of cases of DBD (whose data is always updated by DKK) in Semarang city, by creating the best regression models using stepwise technique. Regression model analysis of results obtained best is Y = 23.029 + 0.004 X1 â€“ 0.074 X2 + 0.070X3, where Y is IR/10000 PDDK, that is the number of residents affected by DBD for each 10000 inhabitants, X1 is the number of residents aged 15-24 years, X2 is total area of land of rice fields and X3 is area of land for buildings and grounds around the page. Keywords: DBD, Characteristics of the Neighborhood, Regression, Stepwise

Penerapan Regresi Logistik Ordinal Proportional Odds Model pada Analisis Faktor-Faktor yang Mempengaruhi Kelengkapan Imunisasi Dasar Anak Balita di Provinsi Aceh Tahun 2015 Budyanra, Budyanra; Azzahra, Ghaida Nasria
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Province of Aceh has basic immunization coverage toddler lowest in Indonesia in 2015. even though, this province has Posyandu and Puskesmas ratio per population of the highest in the western region of Indonesia. This data their concerns regarding immunization coverage has not been handled well in Aceh Province. This papers aims to identify variables that affect the status of complete basic immunization of children aged 12-59 months in Aceh by using ordinal logistic regression analysis. Ordinal logistic regression model used is proportional odds models. Data are obtained from Susenas 2015 that was held in March 2015 by BPS-Statistic of Indonesia. Based on the results of processing data, known only 37.7% of children aged 12-59 months in the province of Aceh in 2015 which gets fully immunized, the remaining 50.6% receive primary immunization but is not complete, even about 11.7% have not received basic immunization at all. From the proportional odds model results showed that the number of children born to mothers (odds ratio = 0.88), maternal age at delivery (odds ratio = 1.03), the level of maternal education (odds ratio = 1.22), and the educational level of the household (odds ratio = 1,2) have a significant impact on the status of complete basic immunization of children. Future studies are expected to include the element of timeliness and add other variables and also with other models in ordinal logistic regression.Keywords:Immunization, Ordinal Logistic Regression, Proportional Odds, Susenas

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

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. Â Keywords : Risk, Stock Return, Panel Data, Least Square Dummy Variable

ANALISIS PERBANDINGAN KINERJA CART KONVENSIONAL, BAGGING DAN RANDOM FOREST PADA KLASIFIKASI OBJEK: HASIL DARI DUA SIMULASI Yogo Aryo Jatmiko; Septiadi Padmadisastra; Anna Chadidjah
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The conventional CART method is a nonparametric classification method built on categorical response data. Bagging is one of the popular ensemble methods whereas, Random Forests (RF) is one of the relatively new ensemble methods in the decision tree that is the development of the Bagging method. Unlike Bagging, Random Forest was developed with the idea of adding layers to the random resampling process in bagging. Therefore, not only randomly sampled sample data to form a classification tree, but also independent variables are randomly selected and newly selected as the best divider when determining the sorting of trees, which is expected to produce more accurate predictions. Based on the above, the authors are interested to study the three methods by comparing the accuracy of classification on binary and non-binary simulation data to understand the effect of the number of sample sizes, the correlation between independent variables, the presence or absence of certain distribution patterns to the accuracy generated classification method. Results of the research on simulation data show that the Random Forest ensemble method can improve the accuracy of classification.

PEMODELAN GENERAL REGRESSION NEURAL NETWORK UNTUK PREDIKSI TINGKAT PENCEMARAN UDARA KOTA SEMARANG Warsito, Budi; Rusgiyono, Agus; Amirillah, M. Afif
MEDIA STATISTIKA Vol 1, No 1 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This paper is discuss about General Regression Neural Network (GRNN) modelling to predict time series data, i.e. the air pollution rate in Semarang City comprises the floating dust, carbon monoxide (CO) and nitrogen monoxide (NO). The GRNN model have four processing layer that are input layer, pattern layer, summation layer and output layer. The input variable is determined by the ARIMA model. The result of GRNN modelling shows that the network have a good performance both at predict in sample and predict out of sample, that can be seen from the mean square error. Â Keywords: GRNN, predict, air pollution Â

PENERAPAN MODEL HYBRID ARIMA BACKPROPAGATION UNTUK PERAMALAN HARGA GABAH INDONESIA Janah, Sufia Nur; Sulandari, Winita; Wiyono, Santoso Budi
MEDIA STATISTIKA Vol 7, No 2 (2014): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Hybrid model discussed in this paper combining ARIMA and backpropagation is applied to grain price forecasting in Indonesia for period January 2008 until April 2013. The grain price time series consists of linear and nonlinear patterns. Backpropagations can recognize non linear patterns that can not be done by ARIMA. In order to find the best model, some combinations of prepocessing transformations, the number of input and hidden units, and the activation function were applied in the contruction of the network structure. Based on the experiments, it can be showed that ARIMA backpropagation hybrid model provides more accurate results than ARIMA model. Â The hybrid model would rather be used in the short-term forecasting, no more than three periods.Â Keywords: ARIMA, Backpropagation, Hybrid, Grain Price

APLIKASI REGRESI PARTIAL LEAST SQUARE UNTUK ANALISIS HUBUNGAN FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DI KOTA YOGYAKARTA Masruroh, Marwah; Subekti, Retno
MEDIA STATISTIKA Vol 9, No 2 (2016): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Human Development Index is one of the indicators to measure the success of a region in the field of human development sector. There are several factors that affect Human Development Index, such as life expentancy, the literacy rate, the average length of the school, and the index of purchasing power. The aim in this paper is to analyze the relationship between factors that affect Human Development Index in Yogyakarta using regression analysis. One of the assumptions of classical regression is not going multicollinierity. Multicollinierity cause misinterpretation of regression coefficients with Ordinary Least Square (OLS) method. One method used to overcome multicollinierity is Partial Least Square (PLS). The result of Human Development Index data analysis showed there was a high correlation between the predictor variables or in other words going multicollinierity, so using PLS method, we obtained adjusted R2 of 99.3% Human Development Index variables can be explained by the four predictor variables. By using PLS method, multicollinierity resolved in the problem of violation in the linear regression assumption.Â Keywords: IPM, OLS, regression, PLS.

DISTRIBUSI POISSON DAN DISTRIBUSI EKSPONENSIAL DALAM PROSES STOKASTIK Sugito, Sugito; Mukid, Moch Abdul
MEDIA STATISTIKA Vol 4, No 2 (2011): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In the queueing system, the processes usually come from a Poisson process. In this system should be obtained an arrival distribution and a service distribution. This paper studies about the form of the number of arrival distribution, the number of service distribution, the interarrival distribution and the service time distribution. Futhermore it talks about the relation of them to a Poisson distribution andÂ an exponential distribution. Â Keywords: Poisson Process, Poisson Distribution, Eksponential Distribution

MODEL REGRESI POISON BIVARIAT DENGAN KOVARIAN KONSTAN Untung Kurniawan
MEDIA STATISTIKA Vol 11, No 1 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Bivariate Poisson models are appropriate for modeling paired count data exhibiting correlation. This study aims to estimates the parameters and test hypothesis of bivariate Poisson regression on modeling the number of infant mortality and maternal mortality in Central Java 2015. The parameters of the bivariate regression model are estimated by using the maximum likelihood method. Results show that the percentage of births by health personnel, the percentage of pregnant women administered the K4 program, the percentage of pregnant women receiving Fe3 tablets, percentage of exclusively breastfed infants, and percentage of households behaved in a clean and healthy life are significant for the number of infant mortality in Central Java. The variables that have significant effect on maternal mortality are percentage of births by health personnel, percentage of maternal women receiving postpartum health services, and percentage of pregnant women receiving Fe3 tablets. Keywords: Bivariate Poisson Regression, Infant Mortality, Maternal Mortality, Maximum Likelihood Estimation

PERSEPSI DUNIA KERJA TERHADAP LULUSAN FRESH GRADUATE S1 MENGGUNAKAN MULTIDIMENSIONAL UNFOLDING (Studi Kasus: Dunia Usaha di Kabupaten Batang) Adhyaksa, M. Atma; Rusgiyono, Agus
MEDIA STATISTIKA Vol 3, No 1 (2010): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Corporate perception of college graduates S1 fresh graduate is a viewpoint held by the world of work regarding the criteria considered in selecting candidates for most job applicants from graduates S1 fresh graduate based on his resume. Perceptions are reviewed based on the configuration of unfolding multidimensional mapping between business entities with the most preferred criteria in the selection process beginning college graduates S1 fresh graduate. Multidimensional unfolding was one of the techniques used in analyzing the proximity between objects is visualized in graphical form in which individuals and stimuli presented in one graph. Â The result is a grade point average, ability and suitability of computer applications course with the working position is most noticed by companies in selecting a job application letter from the college graduates S1 fresh graduate. Â Keywords: Corporate Perception, Fresh Graduate, Multidimensional Unfolding

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