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EARLY STRESS DETECTION DURING PREGNANCY USING E-HEALTH IN THE PANDEMIC

Jurnal Administrasi Kesehatan Indonesia · Vol. 11 No. 2 (2023) · hlm. 288–298

DOI
10.20473/jaki.v11i2.2023.288-298
ISSN
2540-9301, 2303-3592
Terbit
2023-12-02
Penerbit
Universitas Airlangga
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Background: Women are more prone to stress during pregnancy than during the postpartum period. Stress during pregnancy is correlated with pregnancy and birth outcomes. Early detection using the e-health system is an alternative to health services during the pandemic. Aims: The research objective was to produce innovation in early stress detection using an information system based on the e-Health system. Methods: This study was conducted in the Ngaliyan Primary Healthcare Centre with 34 pregnant women. This study utilized both qualitative and quantitative research. Qualitative research used the System Development Life Cycle (SDLC), while quantitative research used an experimental design with a one-shot case study approach. Results: The e-Health system could automatically identify stress during pregnancy, with the TAM questionnaire yielding a very effective result of 85.4%. The average time needed to detect pregnant women's stress was 230.94 seconds. This system can analyze 374 pregnant women within one day (24 hours), provide services, and report pregnant women's stress detection results. Conclusions: The e-Health system effectively conserves time and can be used to record and report early stress in pregnant women. Keywords: early detection, information system, pregnancy, smartphone, stress

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18 penulis · 43 tautan kepenulisan bersama · 27 lintas organisasi

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  • Kementerian Kesehatan Republik Indonesia
  • Politeknik Kesehatan Kemenkes Semarang
  • State University of Semarang
  • Walisongo State Islamic University
  • World Health Organization Regional Office for South-East Asia
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Rekan penulisOrganisasiArtikel bersama
Dhita Aulia OctavianiPoliteknik Kesehatan Kemenkes Semarang2
Bayangsari WedhatamiState University of Semarang1
Waspiah WaspiahState University of Semarang1
Rodiyah RodiyahState University of Semarang1
Rr Sri Endang PujiastutiPoliteknik Kesehatan Kemenkes Semarang1
Sri RahayuKementerian Kesehatan Republik Indonesia1
Arum BudiyatiKementerian Kesehatan Republik Indonesia1
Krisdiana WijayantiKementerian Kesehatan Republik Indonesia1
MundartiKementerian Kesehatan Republik Indonesia1
Nur AbadiWalisongo State Islamic University1
Rr. Sri Endang PujiastutiKementerian Kesehatan Republik Indonesia1
Muflihah IsnawatiPoliteknik Kesehatan Kemenkes Semarang1
Sri WidiyatiPoliteknik Kesehatan Kemenkes Semarang1
Ai TanimizuWorld Health Organization Regional Office for South-East Asia1
Rizky AmeliaState University of Semarang1
Ima Nurcahyanti PutriAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) https://e-journal.unair.ac.id/JAKI/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">EARLY STRESS DETECTION DURING PREGNANCY USING E-HEALTH IN THE PANDEMIC</dc:title>
	<dc:creator>Runjati, Runjati</dc:creator>
	<dc:creator>Rahayu, Sri</dc:creator>
	<dc:subject xml:lang="en-US">pregnancy</dc:subject>
	<dc:subject xml:lang="en-US">stress</dc:subject>
	<dc:subject xml:lang="en-US">early detection</dc:subject>
	<dc:subject xml:lang="en-US">information system</dc:subject>
	<dc:subject xml:lang="en-US">smartphone</dc:subject>
	<dc:subject xml:lang="en-US">Health psychology during pregnancy\</dc:subject>
	<dc:description xml:lang="en-US">Background: Women are more prone to stress during pregnancy than during the postpartum period. Stress during pregnancy is correlated with pregnancy and birth outcomes. Early detection using the e-health system is an alternative to health services during the pandemic.
Aims: The research objective was to produce innovation in early stress detection using an information system based on the e-Health system.
Methods: This study was conducted in the Ngaliyan Primary Healthcare Centre with 34 pregnant women. This study utilized both qualitative and quantitative research. Qualitative research used the System Development Life Cycle (SDLC), while quantitative research used an experimental design with a one-shot case study approach.
Results: The e-Health system could automatically identify stress during pregnancy, with the TAM questionnaire yielding a very effective result of 85.4%. The average time needed to detect pregnant women's stress was 230.94 seconds. This system can analyze 374 pregnant women within one day (24 hours), provide services, and report pregnant women's stress detection results.
Conclusions: The e-Health system effectively conserves time and can be used to record and report early stress in pregnant women.
Keywords: early detection, information system, pregnancy, smartphone, stress</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Airlangga</dc:publisher>
	<dc:date>2023-12-02</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:format>text/xml</dc:format>
	<dc:identifier>https://e-journal.unair.ac.id/JAKI/article/view/43447</dc:identifier>
	<dc:identifier>10.20473/jaki.v11i2.2023.288-298</dc:identifier>
	<dc:source xml:lang="en-US">Indonesian Journal of Health Administration (Jurnal Administrasi Kesehatan Indonesia); Vol. 11 No. 2 (2023): December ; 288-298</dc:source>
	<dc:source>2540-9301</dc:source>
	<dc:source>2303-3592</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://e-journal.unair.ac.id/JAKI/article/view/43447/27141</dc:relation>
	<dc:relation>https://e-journal.unair.ac.id/JAKI/article/view/43447/27371</dc:relation>
	<dc:coverage xml:lang="en-US">Semarang</dc:coverage>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Runjati Runjati; Sri Rahayu</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>