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Application of the Weighted Product Method in a Decision Support System to Determine Children's Multiple Intelligence

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 16 No. 3 (2022) · pp. 251–260

DOI
10.22146/ijccs.70810
ISSN
2460-7258, 1978-1520
Published
2022-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Intelligence cannot solely be measured in terms of intellectual intelligence. There are various types of intelligence in children, which cause teachers and parents require time to determine the type of intelligence of children. Quick and easy decision-making can be achieved using a decision support system. One method that can be adopted in the decision-making process of a decision support system is the weighted product method. This study aims to measure the level of accuracy of the weighted product method in determining the type of multiple intelligence of children. The decision support system determines the type of intelligence of children in early childhood (ages 4-6 years) using Garner's [1] eight types of multiple intelligences as decision-making criteria. The data was collected using interviews and questionnaires to the teachers of Mutiara State Kindergarten. The study found that a decision support system using the weighted product method can determine the type of children's multiple intelligences with an accuracy rate of 96%. Based on the result of analysis and calculation using the weighted product method from test questionnaire data of 55 children, compared to the results of identification by the teacher, it was found that the compatibility of 53 children.

Keywords

Collaboration network of the authors

3 authors · 3 co-authorship links

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  • Universitas Kristen Wira Wacana Sumba
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  • Same organisation
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Application of the Weighted Product Method in a Decision Support System to Determine Children's Multiple Intelligence</dc:title>
	<dc:creator>Fonga Wea Tae, Yuliana Astiti</dc:creator>
	<dc:creator>Kalaway, Rambu Yetti</dc:creator>
	<dc:creator>Leo Lede, Pingky Alfa Ray</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">Multiple Intelligence; Decision Support System; Weighted Product; Mutiara State Kindergarten; Gardner’s types of multiple intelligence</dc:subject>
	<dc:description xml:lang="en-US">Intelligence cannot solely be measured in terms of intellectual intelligence. There are various types of intelligence in children, which cause teachers and parents require time to determine the type of intelligence of children. Quick and easy decision-making can be achieved using a decision support system. One method that can be adopted in the decision-making process of a decision support system is the weighted product method. This study aims to measure the level of accuracy of the weighted product method in determining the type of multiple intelligence of children. The decision support system determines the type of intelligence of children in early childhood (ages 4-6 years) using Garner's [1] eight types of multiple intelligences as decision-making criteria. The data was collected using interviews and questionnaires to the teachers of Mutiara State Kindergarten. The study found that a decision support system using the weighted product method can determine the type of children's multiple intelligences with an accuracy rate of 96%. Based on the result of analysis and calculation using the weighted product method from test questionnaire data of 55 children, compared to the results of identification by the teacher, it was found that the compatibility of 53 children.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US">Universitas Kristen Wira Wacana Sumba</dc:contributor>
	<dc:date>2022-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/70810</dc:identifier>
	<dc:identifier>10.22146/ijccs.70810</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 16, No 3 (2022): July; 251-260</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/70810/34374</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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