Visualization of time series data change by statistical shape analysis

Yukari Shirota, Riri Fitri Sari, Alfan Presekal, Takako Hashimoto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Visualization is very effective when we analyze the big data. When we handle with time series data for a long period, especially visualization is needed. In the paper, we shall illustrate change of the whole trend on time series data as shapes. The method we used is statistical shape analysis which can extract the Affine and non-Affine transformations from the deformation. The method is also helpful to see a local movement of each data sample, compared to other neighbors. In the paper, we illustrate the whole trend change using the Indonesia province comparison concerning the total fertility rate and the under five mortality rate. From the visualization, we found that the relationship between the data have been relatively stable and shows a linear relationship, finally in 2012.

Original languageEnglish
Title of host publication2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728118987
DOIs
Publication statusPublished - Jul 2019
Event16th International Conference on Quality in Research, QIR 2019 - Padang, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

Name2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering

Conference

Conference16th International Conference on Quality in Research, QIR 2019
Country/TerritoryIndonesia
CityPadang
Period22/07/1924/07/19

Keywords

  • Fertility rates
  • Indonesia
  • Mortality rate
  • Province
  • Statistical shape analysis

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