Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal UNP Journal of Statistics and Data Science Journal of Demography, Etnography, and Social Transformation
Atilla Aslanargun
Department of Statistics, Eskisehir Technical University
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Mathematics Social Sciences

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Village Potential Statistics (PODES): Visualization of Schools in Jambi Province with Statistical Programming (R) Fadhlul Mubarak; Atilla Aslanargun; Vinny Yuliani Sundara
Journal of Demography, Ethnography and Social Transformation Vol. 2 No. 2 (2022): Journal of Demography, Etnography and Social Transformation
Publisher : Pusat Kajian Demografi, Etnografi dan Transformasi Sosial

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/demos.v2i2.1333

Abstract

One of the primary data that can be used in research is village potential statistics (PODES). The data was obtained based on research in a certain period by the Statistics Indonesia (BPS). This study aims to visualize the percentage of schools in each city/district in Jambi Province using R programming based on PODES data in 2014 and 2019. In this study, we not only visualize but also how to build attractive graphics and arrange them starting from windows, graphic size, dimensions, color, horizontal axis, vertical axis, and others. Of course, the graph produced in this study is different from the basic plot found in the R program, although the process carried out is also more complicated. From 2014 to 2019, in general, within a period of 5 years there has been an increase in the number of schools in each city/district in Jambi Province. However, from the university level, the number decreased. In 2014 the number of universities in Jambi City was 32 but in 2019 the number decreased to 24. There are even interesting things in Kerinci and Tebo district. In 2014 there were no universities listed, while in 2019 there were 3. This also affects the percentage of education level in each city/district.
Space Time Model in Missing Value Based on Google Trends Data: Gold Price during Covid-19 Fadhlul Mubarak; Vinny Yuliani Sundara; Nurniswah; Atilla Aslanargun
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/534

Abstract

In certain cases, there are data that have a missing value problem. One of them is gold price data from the World Gold Council. The main purpose of this study was to predict gold prices in Austria, India, South Korea, and Turkiye during Covid-19 using the best space-time model on the data. The models that have been used in this research were generalized space-time autoregressive integrated with exogenous variable (GSTARX) and generalized space time autoregressive integrated with exogenous variable (GSTARIX). Before using these models, the last observation carried forward (LOCF) imputation technique solved the missing value problem. In addition, google trends data has been used as an alternative to the spatial weighting matrix and exogenous variables in the two models. And the google trend categories that have been used were google shopping, image search, news search, web search, and youtube search. Based on the smallest mean absolute percentage error (MAPE was 4.3%), GSTARX model in which the weighting matrix has been derived from image search. Relatively speaking, the results of forecasting gold prices in Austria was constant, India was declining, South Korea was declining significantly and Turkiye was incresing significantly.
Co-Authors Mubarak, Fadhlul Nurniswah Sundara, Vinny Yuliani