Visualization of Time Series Data by Statistical Shape Analysis on Fertility Rate and Education in Indonesia

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4 Citations (Scopus)

Abstract

Visualization is very effective when we analyze the time series data. In the paper, we shall illustrate change of the whole trend on time series data as shapes, as well as local changes. The method we used is the statistical shape analysis which can extract separately the Affine and non-Affine transformation parts from the time change deformation. The method is helpful to see a local movement of each landmark data, compared to other neighbors. In the paper, we shall conduct the Indonesia province comparison, concerning the total fertility rate and the education status between 2007 and 2012. From the visualization, we can easily understand the time series changes.

Original languageEnglish
Pages (from-to)60-65
Number of pages6
JournalJournal of Advances in Information Technology
Volume10
Issue number2
DOIs
Publication statusPublished - May 2019

Keywords

  • Affine/non-Affine transformation
  • education level
  • fertility rates
  • partial warp eigenvectors
  • statistical shape analysis

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