Knowledge Transfer About Earthquake Disaster Mitigation To Children Through TF-IDF

Authors

  • Maria Umran Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Selangor
  • Hafiz Mohd. Sarim Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Selangor

DOI:

https://doi.org/10.22373/ekw.v6i2.7281

Keywords:

TF-IDF, disaster mitigation, knowledge transfer

Abstract

Abstract: Past observations during a disaster identify that when children are separated from parents, they suffer due to the inability to comprehend disaster mitigation concepts. This study proposes a process from the existing framework K-Nearest Neighbor (KNN) and Term Frequency - Inverse Document Frequency (TF-IDF) for extracting a large body of knowledge in the form of documents into simple words. Those simple words can be arranged into contextual lyrics utilizing an Artificial Intelligence lyrics generator and then orchestrated into a song using a music generator. The piece, which is the output of the proposed process, is utilized to transfer the knowledge about earthquake disaster mitigation to children. A quantitative analysis of questionnaires on students aged 9-10 in Banda Aceh shows the song's highly significant effect in transferring the knowledge about earthquake disaster mitigation to children.

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Published

2020-12-30

Issue

Vol. 6 No. 2 (2020)

Section

Articles

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