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Media Statistika

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Published by Universitas Diponegoro

ISSN : - EISSN : 24770647 DOI : -

Core Subject : Science,

Decision Sciences, Operations Research & Management

Arjuna Subject : -

Articles 7 Documents

Search results for , issue "Vol 11, No 2 (2018): Media Statistika" : 7 Documents clear

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

PERBANDINGAN METODE REGRESI LINIER MULTIVARIABEL DAN REGRESI SPLINE MULTIVARIABEL DALAM PEMODELAN INDEKS HARGA SAHAM GABUNGAN Ihdayani Banun Afa; Suparti Suparti; Rita Rahmawati
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The composite stock price index or Indonesia Composite Index (ICI) is a composite index of all stocks listed on the Indonesia Stock Exchange and its movements indicate conditions that occur in the capital market. For investors, the ICI movement is one of the important indicator to make a decision whether the stocks will be sold, held or bought new shares. The ICI movement (y) was influenced by several factors including Inflation (x1), Exchange Rate (x2) and SBI interest rate (x3). This study aims to compare the ICI modeling using the parameric and nonparametric approaches, namely multivariable linear regression and multivariable spline regression. Determination of the better model is based on the smaller MSE and the larger R2. The best regression model is multivariable spline regression with x1, x2 and x3, each with a sequence orde (3,2,2) and the number of knot points (1,2,2).Keywords: Indonesia Composite Index, Multiple Linear Regression, Multivariable Spline Regression, MSE, R2

KAJIAN STATISTICAL DAN COST EFFICIENCY DALAM PENENTUAN GUGUS SAMPEL BLOK SENSUS TERBAIK (Studi Kasus: Sampling Design Susenas-2015 di Kabupaten Natuna) Wiwik Andriyani Lestari Ningsih; I Made Arcana
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Two aspects of efficiency that should be considered in applying sampling design of a survey are statistical efficiency and cost efficiency. Efficiency in statistical aspect improves precision of estimators obtained by the survey data, whereas efficiency in cost aspect provides an economic survey. The purpose of this researchis to evaluate the both efficiencies in all possible census blocks (CBs) sample setand to identify the best CBs sample set in the 2015 National Socio-Economic Survey (Susenas). Therefore, a computer program for calculating statistical, and cost efficiency aspects was developed in this research to determine the best sampel set of CBs among all possible sampel set of CBs based on sampling design of the 2015 Susenas implemented in Natuna District, Kepulauan Riau Province. The best possible sample set of CBs is determinedby considering statistical efficiency aspect, cost efficiency aspect, as well as combination of those two aspects. The result showed that the best sample set of CBs on statistical efficiency aspect provided the CBs sample set having minimum value of RSE index; evaluation on cost efficiency aspect provided the best CBs sample set having minimum value of total cost esimated using the total score of accessibility index; and evaluation on both efficiency aspects provided the best CBs sample set having minimum value of RSE index and minimum value of total score of accessibility index. Keywords: sampling design, all possible samples, statistical efficiency, cost efficiency

CREDIT SCORING MENGGUNAKAN METODE LOCAL MEANS BASED K HARMONIC NEAREST NEIGHBOR (MLMKHNN) Tatik Widiharih; Moch Abdul Mukid
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Credit Scoring is designed so that lenders can easily make decisions regarding whether a loan proposal from a prospective customer is worthy of approval or not. This study examines the application of the Multi Local Means Based K Harmonic Nearest Neighbor (MLMKHNN) method in the case of motorcycle credit in a financial institution. The classification capability of this method in detecting potential borrowers into the credit category is either good or bad compared to its previous method, Local Means Based K Harmonic Nearest Neighbor (LMKNN). In this case the MLMKHNN method has not shown better performance than the LMKNN method. At the same level of total accuracy, MLMKHNN requires more numbers of neighbors than the number of neighbors required by the LMKNN method. Keywords: sampling design, all possible samples, statistical efficiency, cost efficiency

DETERMINAN IMPOR SERAT KAPAS DI INDONESIA TAHUN 1975-2014 (PENDEKATAN ERROR CORRECTION MECHANISM) Nida'ul Hanifah; Fitri Kartiasih
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The activity of textile sector and textile product (TPT) in Indonesia keeps growing from year to year.TPTIndustry has become the main contributor of foreign exchange from non-oil and gas sector. Unfortunately, the domestic supply of cotton fiber, main material of textile product, can’t fulfill textile industry’s demand. It forces the nation to import the raw materials. Based on the problem about the import that still exist until the present, it is necessary to do a research to analyze the development of cotton fiber import in Indonesia and to identify the factors affecting the development of Indonesian cotton fiber imports during 1975-2014. This research uses descriptive analysis and inference analysis. The descriptive analysis method used in this research is graphical analysis, while the inference analysis is Error Correction Mechanism (ECM) method. Based on the estimation made with ECM, it was found that 5 variables significantly affect the cotton import volume in the long term, including: real per capita Gross Domectic Product (GDP), international cotton fiber prices, domestic cotton fiber production, the demand of cotton fiber by domestic yarn spinning industry and textile product exports volume. While in short term, only 4 variables significantly affect thecotton fiber import volume: domestic cotton fiber production,the demand of cotton fiber by domestic yarn spinning industry, real per capita GDP and textile product exports volume. Keywords: import, cotton fiber, Textile Industry and Textile Product (TPT),Error Correction Mechanism (ECM).

ANALYSIS OF THE NUMBER INFANT AND MATERNAL MORTALITY IN CENTRAL JAVA INDONESIA USING SPATIAL-POISSON REGRESSION Alan Prahutama; Budi Warsito; Moch. Abdul Mukid
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Maternal and infant mortality are one of the most dangerous problems of the community since it can profoundly affect the number and composition of the population. Currently, the government has been taking heed on the attempt of reducing the number of maternal and newborn mortality in Central Java which requires data and information entirely. Poisson regression is a nonlinear regression that is often used to model the relationship between response variables in the form of discrete data with predictor variables in the form of discrete or continuous data. In space analysis, GWPR is one of method in space modeling which can model regional-based regression. It is based on some factors including the number of health facilities, the number of medical personnel, the percentage of deliveries performed with non-medical assistance; the average age of a woman's first marriage; the average education level of married women; average amount of per capita household expenditure; percentage of village status; the average rate of exclusive breastfeeding; percentage of households that have clean water and the percentage of poor people. Based on the analysis, it is revealed that the determinants of maternal and infant mortality in Central Java using Poisson and GWPR models, among others are the number of health facilities, the number of medical personnel, the average number of per capita household expenditure and the percentage of the poor. In the maternal and infant mortality model, the AIC value of GWPR model produces better modeling than Poisson regression. Keywords: Maternal and Infant mortality, Poisson, GWPR

Front Matter Vol. 11 No. 2 2018 Statistika, Media
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

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