Elkawnie
Vol 6, No 2 (2020)

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

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)



Article Info

Publish Date
30 Dec 2020

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.

Copyrights © 2020






Journal Info

Abbrev

elkawnie

Publisher

Subject

Biochemistry, Genetics & Molecular Biology Engineering

Description

Elkawnie is a journal of Integration Science and Technology with Islam. It's covering research and technology in the field of study of Architecture, Biology, Chemistry, Environmental Engineering, ICT, Physical Engineering and other science and technology field. In particular, Elkawnie's journal ...