Vector machine OVA-RFE approach for finding the significant plants of jamu

Aries Fitriawan, Ito Wasito, Wisnu Ananta Kusuma, Rudi Heryanto

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

Abstract

Jamu medicines are popular traditional medicines from Indonesia. Jamu made from a mixture of several plants. Jamu formula are based on empirical data and personal experiences, so it needs to systemize the formulation of Jamu and develop basic scientific principles of Jamu for Indonesian Healthcare System. The purpose of this research is to find the Jamu plants that have the most significant effect on the diseases. We proposed a feature selection approach using SVM OVA-RFE. We also added the previous Jamu feature selection research using K-Means and PLS-DA for comparison. The SVM OVA-RFE method successfully reduced the data dimension into 3085 of Jamu samples and 238 species of plants. The result from SVM classification using OVA-RFE outperform the previous researches.

Original languageEnglish
Title of host publication2016 6th International Workshop on Computer Science and Engineering, WCSE 2016
PublisherInternational Workshop on Computer Science and Engineering (WCSE)
Pages650-654
Number of pages5
ISBN (Electronic)9789811100086
Publication statusPublished - 1 Jan 2016
Event2016 6th International Workshop on Computer Science and Engineering, WCSE 2016 - Tokyo, Japan
Duration: 17 Jun 201619 Jun 2016

Publication series

Name2016 6th International Workshop on Computer Science and Engineering, WCSE 2016

Conference

Conference2016 6th International Workshop on Computer Science and Engineering, WCSE 2016
CountryJapan
CityTokyo
Period17/06/1619/06/16

Keywords

  • Feature selection
  • Jamu
  • Machine learning
  • Recursive feature elimination
  • SVM OVA-RFE.

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