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An Analysis of Problem Solving Ability using mathematical modeling strategies in Brain-Based Learning

Unnes Journal of Mathematics Education · Vol. 8 No. 3 (2019) · hlm. 173–180

DOI
10.15294/ujme.v8i3.32218
ISSN
2460-5840, 2252-6927
Terbit
2019-11-30
Penerbit
Department of Mathematics, Universitas Negeri Semarang
Bahasa
eng

Abstrak

Problem-solving ability learning (PSA) is a fundamental problem that needs to be developed in learning mathematics at school. In this research mathematical modeling strategies (MMS) are developed for problem solving. This study aims to investigate how the implementation of MMS for problem-solving in mathematics learning. This study was conducted at SMP Negeri 34 Semarang. This research used sequential explanatory design. The quantitative research design is a quasi experimental design with the nonequivalent posttest-only control group design. Data collection techniques used in this study are documentation, tests, scale, interview, and observation, then processed with a classical completeness test, t-test, and proportion test. The results of this study indicate that (1) PSA on the application of mathematical modelling strategies on Brain-Based Learning (BBL) has achieved classical mastery learning; (2) the PSA of the experimental class by applying mathematical modeling strategies to Brain-Based Learning is better than the control class that uses the Problem Based Learning; and (3) two subjects with high category self-efficacy (SE) have high PSA, two SE subjects are categorized having middle PSA, and two low SE subjects have a low PSA.

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  • State University of Semarang
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Rekan penulisOrganisasiArtikel bersama
Insyiraah Oxaichiko ArissintaState University of Semarang1
Sabrina Aziz AuliaState University of Semarang1
Muhamad Abdul Qodir DaniState University of Semarang1
Galih Kusuma WijayaState University of Semarang1
St. Budi WaluyaAfiliasi tidak diketahui1
MulyonoState University of Semarang1
Noviana Dini RahmawatiState University of Semarang1
Mira Dwi UtamiState University of Semarang1
Nike Yustina OktavianiState University of Semarang1
Luthfiyah AstutiningtyasState University of Semarang1
Riska Nur FitrianingsihState University of Semarang1
Iwan JunaediState University of Semarang1
Sanianajiba Nugroho PutriState University of Semarang1
Hendrik SutrisnoState University of Semarang1
Yeni NurochmahState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/ujme/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 6 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">An Analysis of Problem Solving Ability using mathematical modeling strategies in Brain-Based Learning</dc:title>
	<dc:creator>Rahman, Alif Aulia</dc:creator>
	<dc:creator>Kharisudin, Iqbal</dc:creator>
	<dc:description xml:lang="en-US">Problem-solving ability learning (PSA) is a fundamental problem that needs to be developed in learning mathematics at school. In this research mathematical modeling strategies (MMS) are developed for problem solving. This study aims to investigate how the implementation of MMS for problem-solving in mathematics learning. This study was conducted at SMP Negeri 34 Semarang. This research used sequential explanatory design. The quantitative research design is a quasi experimental design with the nonequivalent posttest-only control group design. Data collection techniques used in this&amp;nbsp;study&amp;nbsp;are documentation, tests, scale, interview, and observation, then processed with a classical completeness test, t-test, and proportion test. The results of this study indicate that (1) PSA on the application of mathematical modelling strategies on Brain-Based Learning (BBL) has achieved classical mastery learning; (2) the PSA of the experimental class by applying mathematical modeling strategies to Brain-Based Learning is better than the control class that uses the Problem Based Learning; and (3) two subjects with high category self-efficacy (SE) have high PSA, two SE subjects are categorized having middle PSA, and two low SE subjects have a low PSA.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Mathematics, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2019-11-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/sju/ujme/article/view/32218</dc:identifier>
	<dc:identifier>10.15294/ujme.v8i3.32218</dc:identifier>
	<dc:source xml:lang="en-US">Unnes Journal of Mathematics Education; Vol 8 No 3 (2019): Unnes Journal of Mathematics Education; 173-180</dc:source>
	<dc:source>2460-5840</dc:source>
	<dc:source>2252-6927</dc:source>
	<dc:source>10.15294/ujme.v8i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/ujme/article/view/32218/15169</dc:relation>
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