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Exploring Election and Census Highly Informative Data Nationally for Indonesia ( Eechidna R package)

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FahroziFahrozi edited this page Apr 1, 2019 · 5 revisions

Background

An election is one of the main pillars of an accumulation of people's will, General Election as well as a democratic procedure for choosing leaders.

In Indonesia, elections are a matter of great waiting because it is a party of democracy for all people to choose leaders of their choice. Elections also generate data which is of great public interest, but often not easy to access or work with. R is a language and environment for statistical computing and graphics and R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. R makes data analysis accessible to everyone and, of course, can help us to answer questions about data.

Among the many packages available for R, there is a package called eechidna (Exploring Election and Census Highly Informative Data Nationally for Australia). This package makes it easy to look at the data from several years worth of Australian Censuses and Federal Elections. Functions in the package can be used to pull the most recent election and Census data, and future changes. [1].

The main goal of my project is to explore the elections and census data from The Indonesian Central Bureau of Statistics (BPS). I aim to produce an eechidna-like package for Indonesia. For information, the presidential and vice presidential elections in Indonesia are carried out 4 years and the data that will be used in this project is data on the results of the presidential and vice-presidential elections in Indonesia in 2004, 2009 and 2014 and demograpic data for Indonesia as well. The data includes voting results for each polling booth and electoral division (electorate). I plan to show a few typical methods to explore these data.

Related work

Another package that provided in R software related to the election is the elections library.this package is also good because it analyzes the US presidential election and as well as possible predictors. But for the results of the analysis, this package is not very complete. If we consider the eechidna package for results the analysis can be more complete and detailed such as election result, census data such as aging population, mapping electoral division, and modeling election result.

Some common eechidna strategies analyses include:

Details of your coding project

I plan to produce a package like the eechidna package, but for Indonesia. It will include the raw data, and several vignettes with visualisations that explore the data to answer common questions about voting patterns.

Expected impact

  • The most ambitious impact of this project would be to successfully generate a dataset similar to the eechidna package, but for Indonesia. Even more, and get enough information about analysis of the election data and can be the recommended information for the government for the future.

Mentors

  1. Prof. Ben Marwick - is an Associate Professor of Archaeology in University of Washington and he is also Affiliate faculty in the Center for Statistics and Social Science and one of the original developers and maintainer of the eechidna package.
  2. Mr. Jeremy Forbes - has greatly expanded the eechidna package recently, and he is an Honours student in Econometrics and Business Statistics at Monash University.

Student

  • Fahrozi - ozifahrozi2@gmail.com - MSc candidate in applied mathematics at Budapest University of Technology and Economics

References

[1] The power of R: Professor Dianne Cook elected to esteemed R Foundation, The Authors, 2016. https://www.monash.edu/business/news-and-events/2016/the-power-of-r-professor-dianne-cook-elected-to-esteemed-r-foundation.

[2] Forbes, Jeremy; An Introduction to Exploring Election and Census Highly Informative Data Nationally for Australia, 2017. https://cran.r-project.org/web/packages/eechidna/vignettes/eechidna-intro.html#modelling-election-results-using-census-data.

[3] Marwick,Ben;Cook,Di; Hofmann,Heike; Hyndman,Rob ; Sievert,Carson; Tierney,Nicholas; Zhou,Fang, Exploring the 2013 Election data 2018. https://mran.microsoft.com/snapshot/2018-03-22/web/packages/eechidna/vignettes/exploring-election-data.html#which-candidate-did-the-best.

[6] Willem M. van der Wal, elections: USA Presidential Elections Data, 2018. https://cran.r-project.org/web/packages/elections/index.html.

[7] Ferris, Ryan ,Presidential Election Turnout Chart:1920:2016, 2019. https://www.bellinghampoliticsandeconomics.com/2019/01/presidential-election-turnout.html.

[9] Badan Pusat Statistik, Persentase Hasil Perhitungan Suara Sah Pemilu Presiden/Wakil Presiden Tahun 2014 Menurut Provinsi, 2017. https://www.bps.go.id/statictable/2009/03/04/1574/hasil-perhitungan-suara-sah-pemilu-presiden-wakil-presiden-putaran-pertama-tahun-2004-2009-2014.html.

[10] BKKBN, Demographic data for Indonesia, 2019. http://aplikasi.bkkbn.go.id/mdk/MDKReports/Default_Anonymous.aspx.

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