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Maria Umran
Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Selangor
Biochemistry, Genetics & Molecular Biology Engineering

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Knowledge Transfer About Earthquake Disaster Mitigation To Children Through TF-IDF Maria Umran; Hafiz Mohd. Sarim
Elkawnie: Journal of Islamic Science and Technology Vol 6, No 2 (2020)
Publisher : Universitas Islam Negeri Ar-Raniry Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/ekw.v6i2.7281

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.
Co-Authors Hafiz Mohd. Sarim