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Technopreneurship in Healthcare: Evaluating User Satisfaction and Trust in AI-Driven Safe Entry Stations

Aptisi Transactions on Technopreneurship (ATT) · Vol. 6 No. 3 (2024)

DOI
10.34306/att.v6i3.489
ISSN
2656-8888, 2655-8807
Terbit
2024-09-13
Penerbit
Pandawan
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

The development of technology in the health sector has encouraged the adoption of technopreneurship, especially in the application of artificial intelligence (AI) to support the safety and efficiency of health services. One of the innovations that has emerged is the AI-driven Safe Entry Station, which is designed to improve the safety and comfort of patients and medical personnel. However, the success of implementing this technology is highly dependent on the level of user satisfaction and trust. This study aims to evaluate the level of user satisfaction and trust in Safe Entry Stations in the health care environment and also explore the variables that influence the acceptance of this technology among users. This research method uses a quantitative approach with a survey involving 673 respondents from various health institutions that have used Safe Entry Stations. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS 4.0 software to identify the relationship between User Satisfaction (US), trust (TR), behaviour intention (BI), usage behaviour (SB) and technopreneurial impac (TI). The results showed that US and TR significantly influences BI and UB. Additionally, BI strongly impacts TI, suggesting that stronger intentions lead to a greater perceived impact on technopreneurship. This study found that AI-driven Safe Entry Stations has great potential for widespread adoption in the healthcare sector. These findings provide important insights for further development of this technology as well as technopreneurship strategies in the healthcare sector.

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  • Universitas Raharja
  • Satya Wacana Christian University
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Danny ManonggaSatya Wacana Christian University15
Ninda LutfianiUniversitas Raharja14
Irwan SembiringSatya Wacana Christian University12
Nuke Puji Lestari SantosoUniversitas Raharja9
Alfiah KhoirunisaUniversitas Raharja9
Agung RizkyAfiliasi tidak diketahui5
Sutarto WijonoAfiliasi tidak diketahui4
Dwi ApriliasariAfiliasi tidak diketahui4
Ihsan Nuril HikamAfiliasi tidak diketahui4
Adam FaturahmanAfiliasi tidak diketahui4
Untung RahardjaUniversitas Raharja3
Muhtarom MuhtaromAfiliasi tidak diketahui3
Nesti Anggraini SantosoAfiliasi tidak diketahui3
Natasya Aprila YusufAfiliasi tidak diketahui3
Alwiyah AlwiyahAfiliasi tidak diketahui3
Eka Purnama HarahapUniversitas Raharja3
Marviola HardiniAfiliasi tidak diketahui3
Nuke Puji Lestari SantosoAfiliasi tidak diketahui3
Yulia Putri Ayu SanjayaAfiliasi tidak diketahui3
Desy AprianiAfiliasi tidak diketahui2
Mohamad RakhmansyahAfiliasi tidak diketahui2
Umi NarimawatiAfiliasi tidak diketahui2
Joko SiswantoAfiliasi tidak diketahui2
Hindriyanto Dwi PurnomoSatya Wacana Christian University2
Fitra Putri OgandaUniversitas Raharja2
Tarisya RamadhanAfiliasi tidak diketahui2
Aan KaniviaAfiliasi tidak diketahui2
Muhammad Faizal FazriAfiliasi tidak diketahui2
Izwan AmsyarAfiliasi tidak diketahui2
Haznah LatifahAfiliasi tidak diketahui2
Zaleha FauziahAfiliasi tidak diketahui2
Raihan RaihanAfiliasi tidak diketahui2
Nanda SeptianiAfiliasi tidak diketahui2
Fauziyyah Husna Nurdiayanah LestariAfiliasi tidak diketahui2
Farida AgustinAfiliasi tidak diketahui2

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://att.aptisi.or.id/index.php/att/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">Technopreneurship in Healthcare: Evaluating User Satisfaction and Trust in AI-Driven Safe Entry Stations</dc:title>
	<dc:creator xml:lang="en">Rahardja, Untung</dc:creator>
	<dc:creator xml:lang="en">Sunarya, Po Abas</dc:creator>
	<dc:creator xml:lang="en">Aini, Qurotul</dc:creator>
	<dc:creator xml:lang="en">Millah, Shofiyul</dc:creator>
	<dc:creator xml:lang="en">Maulana, Sabda</dc:creator>
	<dc:subject xml:lang="en">Technopreneurship</dc:subject>
	<dc:subject xml:lang="en">Healthcare</dc:subject>
	<dc:subject xml:lang="en">Satisfaction</dc:subject>
	<dc:subject xml:lang="en">Trust</dc:subject>
	<dc:subject xml:lang="en">Safe Entry Stations</dc:subject>
	<dc:description xml:lang="en">The development of technology in the health sector has encouraged the adoption of technopreneurship, especially in the application of artificial intelligence (AI) to support the safety and efficiency of health services. One of the innovations that has emerged is the AI-driven Safe Entry Station, which is designed to improve the safety and comfort of patients and medical personnel. However, the success of implementing this technology is highly dependent on the level of user satisfaction and trust. This study aims to evaluate the level of user satisfaction and trust in Safe Entry Stations in the health care environment and also explore the variables that influence the acceptance of this technology among users. This research method uses a quantitative approach with a survey involving 673 respondents from various health institutions that have used Safe Entry Stations. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS 4.0 software to identify the relationship between User Satisfaction (US), trust (TR), behaviour intention (BI), usage behaviour (SB) and technopreneurial impac (TI). The results showed that US and TR significantly influences BI and UB. Additionally, BI strongly impacts TI, suggesting that stronger intentions lead to a greater perceived impact on technopreneurship. This study found that AI-driven Safe Entry Stations has great potential for widespread adoption in the healthcare sector. These findings provide important insights for further development of this technology as well as technopreneurship strategies in the healthcare sector.</dc:description>
	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2024-09-13</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">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://att.aptisi.or.id/index.php/att/article/view/489</dc:identifier>
	<dc:identifier>10.34306/att.v6i3.489</dc:identifier>
	<dc:source xml:lang="en">Aptisi Transactions on Technopreneurship (ATT); Vol. 6 No. 3 (2024): November; 404−417</dc:source>
	<dc:source xml:lang="id">Aptisi Transactions On Technopreneurship (ATT); Vol 6 No 3 (2024): November; 404−417</dc:source>
	<dc:source>2656-8888</dc:source>
	<dc:source>2655-8807</dc:source>
	<dc:source>10.34306/att.v6i3</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://att.aptisi.or.id/index.php/att/article/view/489/284</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2024 Untung Rahardja, Po Abas Sunarya, Qurotul Aini, Shofiyul Millah, Sabda Maulana</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>