Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

Media Statistika

media_statistika
Website

Published by Universitas Diponegoro

ISSN : - EISSN : 24770647 DOI : -

Core Subject : Science,

Decision Sciences, Operations Research & Management

Arjuna Subject : -

Articles 220 Documents

1 2 3 4 5

INFERENSI DATA UJI HIDUP TERSENSOR TIPE II BERDISTRIBUSI RAYLEIGH Widiharih, Tatik; Mardjiyati, Wiwin
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Abstrak Analisis data uji tahan hidup merupakan salah satu teknik analisis statistika yang banyak digunakan di bidang industri dan kesehatan. Data waktu hidup dapat berupa data lengkap atau data tersensor, dan merupakan variabel random nonnegatif. Estimator titik untuk parameter q digunakan MLE, kemudian MLE tersebut digunakan untuk uji kecocokan distribusi Rayleig dengan metode Anderson Darling. Estimator titik uji tahan hidup meliputi rata-rata waktu kegagalan (mean time to failure / MTTF), fungsi kegagalan h(t), dan fungsi ketahanan S(t). Estimasi interval dilakukan dengan metode besaran pivot. Â Kata kunci: data tersensor, MLE, rata-rata waktu kegagalan, fungsiÂ Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â kegagalan, fungsi ketahanan

ESTIMASI PARAMETER PADA SISTEM MODEL PERSAMAAN SIMULTAN DATA PANEL DINAMIS DENGAN METODE 2 SLS GMM-AB Arya Fendha Ibnu Shina
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data. Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations

GRAFIK PENGENDALI NON PARAMETRIK EMPIRIK Santoso, Rukun
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Shewhart control chart is constructed base on the normality assumption of process.Â If the normality is fail then the empirical control chart can be an alternative solution. This means that the control chart is constructed base on empirical density estimator. In this paper the density function is estimated by kernel method.Â The optimal bandwidth is selected by leave one out Cross Validation method. The result of empirical control chart will be compared to ordinary Shewhart chart. Â Key words : Control chart, Kernel, Cross Validation

IDENTIFIKASI AUTOKORELASI SPASIAL PADA JUMLAHPENGANGGURAN DI JAWA TENGAH MENGGUNAKAN INDEKS MORAN Wuryandari, Triastuti; Hoyyi, Abdul; Kusumawardani, Dewi Setya; Rahmawati, Dwi
MEDIA STATISTIKA Vol 7, No 1 (2014): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Unemployment is caused by the work force or job seekers are not proportional with the number of existing jobs. Unemployment is often a problem in the interconnected economy due to unemployment, productivity and income will be reduced. The number of unemployed in an are Â Â Â Â Â a expected to be affected by unemployment in the surrounding area. This is made â€‹â€‹possible because of the proximity factor or adjacency between regions, it is estimated that there are linkages to the regional unemployment rate. To determine the relationship between regional linkages used Moranâ€™s Index method. The number of unemployed in Central Java, obtained Moranâ€™s Index value = 0.0614. Moran's Index valuesâ€‹â€‹ in the range 0 < I â‰¤ 1 indicating the presence of spatial autocorrelation is positive but small correlation can be said because of near zero, orit can be concluded that the similarity between the district does not have a value or indicate that unemployment among districts in Central Java has a small correlation.Keywords: Unemployment, Moranâ€™s Index, Central Java, Autocorrelation, Spatial

BAGGING CLASSIFICATION TREES UNTUK PREDIKSI RISIKO PREEKLAMPSIA (Studi Kasus : Ibu Hamil Kategori Penerima Jampersal di RSUD Dr. Moewardi Surakarta) Mukid, Moch. Abdul; Wuryandari, Triastuti; Ratnaningrum, Desy; Sri Rahayu, Restu
MEDIA STATISTIKA Vol 8, No 2 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Preeclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy. Classification Trees is a statistical method that can be used to identify potency of expectant women suffering from preeclampsia. This research aim to predict the risk of preeclampsia based on some individual variables. They are parity, work status, history of hypertension of preeclampsia, body mass index, education and income. To improve the stability and accuracy of the prediction were used the Bootstrap Aggregating Classification Trees method. By the method, classification accuracy reach to 86%.Keywords : Pre-eclampsia, Bagging CART, Classification Accuracy

BAGGING REGRESI LOGISTIK ORDINAL PADA STATUS GIZI BALITA Akbar, Muhammad Sjahid; Mukarromah, Adatul; Paramita, Lalita
MEDIA STATISTIKA Vol 3, No 2 (2010): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

World Health Organization-National Centre for Health Statistic (WHO-NCHS) is standart nutritional status used in Indonesia, it based on Kartu Menuju Sehat (KMS). These Indices can be expressed in terms of Z-score based Weight-for-Age. This Indices need comparison considering the fact which cause nutritional status not only Weight-for-Age. The aim from this research to obtain bagging ordinal logistics regression for WHO-NCHS nutritional status and new nutritional status. A new nutritional status expressed in terms of cluster, while classification function expressed from logit model of ordinal logistics regression. The result for new nutritional status bagging obtained at 60 bootstrap replicated that is 76.345%, this model can decrease misclassification until 22.046%. While bagging for WHO-NCHS nutritional status can increase accurate classification from single data set 75.863% at 150 bootstrap replicated. Â Keywords: Child nutritional status, Bagging, Ordinal logistics regression.

PERAMALAN BEBAN LISTRIK DAERAH ISTIMEWA YOGYAKARTA DENGAN METODE SINGULAR SPECTRUM ANALYSIS (SSA) Herni Utami; Yunita Wulan Sari; Subanar Subanar; Abdurakhman Abdurakhman; Gunardi Gunardi
MEDIA STATISTIKA Vol 12, No 2 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This paper will study forecasting model for electricity demand in Yogyakarta and forecast it for 2019 until 2024. Usually, electricity demand data contain seasonal. We propose Singular Spectral Analysis-Linear Recurrent Formula (SSA-LRF) method. The SSA process consists of decomposing a time series for signal extraction and then reconstructing a less noisy series which is used for forecasting. The SSA-LRF method will be used to forecast h-step ahead. In this study, we use monthly electricity demand in Yogyakarta for 11 year (2008 to 2018). The forecasting results indicates that the forecast using window length of L=26 have good performance with MAPE of 1.9%.

ESTIMASI PARAMETER MODEL MIXTURE AUTOREGRESSIVE (MAR) MENGGUNAKAN ALGORITMA EKSPEKTASI MAKSIMISASI (EM) Asrini, Mika; Sulandari, Winita; Wiyono, Santoso Budi
MEDIA STATISTIKA Vol 6, No 1 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Mixture autoregressive (MAR) Model is a mixture of Gaussian autoregressive (AR) components. The mixture model is capable for modelling of nonlinear time series with multimodal conditional distributions. This paper discusses about the parameters estimation using EM algorithm. All possible models are then applied to national maize production data. In this case, the BIC is used for the MAR model selection. Keywords : Mixture Autoregressive, EM Algorithm, BIC, Maize Production

ANALISIS SPASIAL PENGARUH TINGKAT PENGANGGURAN TERHADAP KEMISKINAN DI INDONESIA (Studi Kasus Provinsi Jawa Tengah) Rahmawati, Rita; Safitri, Diah; Fairuzdhiya, Octafinnanda Ummu
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Poverty is still being one of big problems in Indonesia. Any efforts are done to find a solution for this problem. Poverty itself can be caused of the high unemployment that occurs. With a number of unemployment, it will be lower income thus reducing also purchasing power and the ability to meet the needs of life thus causing poverty. This study analyzed the impact of unemployment to the poverty as involving spatial factors, using spatial regression analysis. Used data on poverty and unemployment in each regency in the central java, the analysis shows that based on likelihood ratio test, obtained LR test value 6,038 or p-value 0,014001 which means there is a spatial correlation. By testing model simultaneously nor individually using Breusch-Pagan test and Wald test, it show that both are significant, with BP = 6,7094; df = 1; p-value = 0,009591 and Wald statistic = 7,0238; p-value = 0,0080434. The results means there are spatial element in the relations between unemployment and poverty in central java so that SEM is more proper used than ordinary linear regression.Â Keywords: Spatial Error Model (SEM), Spatial Autocorrelation, Spatial Heterogeneity

ANALISIS REGRESI SPASIAL DAN POLA PENYEBARAN PADA KASUS DEMAM BERDARAH DENGUE (DBD) DI PROVINSI JAWA TENGAH Fatati, Inna Firindra; Wijayanto, Hari; Sholeh, Agus M.
MEDIA STATISTIKA Vol 10, No 2 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dengue Hemorrhagic Fever (DHF) is one of the diseases that threaten human health. The cases of dengue fever in the district / city certainly has different characteristics, geographic condition, the potential of the region, health facilities, as well as other matters that lie behind them. Based on local moran index values are visualized through thematic maps, some area adjacent quadrant tends to be in the same group. There are two significant quadrant in describing the pattern of spread of dengue cases namely quadrant high-high and lowlow. This indicates a spatial effect on the number of dengue cases, so that the spatial regression analysis. Based on the value ofÂ and AIC, autoregressive spatial models (SAR) is good enough to be used in modeling the number of dengue cases in the province of Central Java. Factors that influence the number of dengue cases Central Java province in 2015 is the number of health centers per 1000 population, the number of polindes per 1000 population, population density (X3), percentage of people with access to drinking water sustainable decent (X6), the percentage of water quality net free of bacteria, fungi and chemicals (X7), and the number of facilities protected springs (X8).

Page 2 of 22 | Total Record : 220

1 2 3 4 5

Filter by Year

2008 2023

Filter By Issues

All Issue Vol 16, No 1 (2023): Media Statistika (Forthcoming Issue) Vol 15, No 2 (2022): Media Statistika Vol 15, No 1 (2022): Media Statistika Vol 14, No 2 (2021): Media Statistika Vol 14, No 1 (2021): Media Statistika Vol 13, No 2 (2020): Media Statistika Vol 13, No 1 (2020): Media Statistika Vol 12, No 2 (2019): Media Statistika Vol 12, No 1 (2019): Media Statistika Vol 11, No 2 (2018): Media Statistika Vol 11, No 1 (2018): Media Statistika Vol 10, No 2 (2017): Media Statistika Vol 10, No 1 (2017): Media Statistika Vol 9, No 2 (2016): Media Statistika Vol 9, No 1 (2016): Media Statistika Vol 8, No 2 (2015): Media Statistika Vol 8, No 1 (2015): Media Statistika Vol 7, No 2 (2014): Media Statistika Vol 7, No 1 (2014): Media Statistika Vol 6, No 2 (2013): Media Statistika Vol 6, No 1 (2013): Media Statistika Vol 5, No 2 (2012): Media Statistika Vol 5, No 1 (2012): Media Statistika Vol 4, No 2 (2011): Media Statistika Vol 4, No 1 (2011): Media Statistika Vol 3, No 2 (2010): Media Statistika Vol 3, No 1 (2010): Media Statistika Vol 2, No 2 (2009): Media Statistika Vol 2, No 1 (2009): Media Statistika Vol 1, No 2 (2008): Media Statistika Vol 1, No 1 (2008): Media Statistika More Issue

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota semarang,

Jawa tengah

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name -

Contact Email -

Phone -

Journal Mail Official -

Editorial Address -

Location Kota semarang, Jawa tengah INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
-

Contact Email
-

Phone
-

Journal Mail Official
-

Editorial Address
-

Location
Kota semarang,

Jawa tengah

INDONESIA