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Consumer Acceptance Analysis of Purchase Interest Using Live Features on The Marketplace with Technology Acceptance Model (TAM) Method Case Study: Shopee

Journal of Advances in Information Systems and Technology · Vol. 5 No. 2 (2024) · hlm. 207–221

DOI
10.15294/jaist.v5i2.61455
ISSN
2715-999X, 2714-9714
Terbit
2024-01-23
Penerbit
Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

The development of technology has become one of the instant lifestyles of the community because it has high mobility in carrying out daily activities. The use of the internet for commercial transactions is known as electronic commerce (e-Commerce). In 2021 Shopee launched a new feature before other competitors had the Shopee live feature. This research is more focused on analyzing buyers using the Shopee live feature on the Shopee marketplace using the Technology Acceptance Model (TAM). The purpose of this study is to analyze how the influence of consumers in buying interest using the Shopee live feature and to determine the effect of each variable used. This type of research is quantitative research. The research sample was 255 UNNES student respondents from 2015-2019. The data analysis method used is descriptive analysis using SEM with SmartPLS 3.0 software. The data that has been obtained is done data cleaning. It was found that the valid data were 203 people. The results of the research based on what has been done on the outer model, there are three indicators that are deleted, namely PEOU 2, PEOU 4, and PU 5, because the results obtained are still below the set value BI because this hypothesis has a value less than the standard value of the t-test so it is rejected. However, there are six accepted hypotheses, namely PE > PU, PE > PEOU, PE > BI, PT > PU, PT > BI, and PU > BI. Based on the results of this analysis, the six variables have factors that influence the purchase intention using the Shopee live feature.

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Rekan penulisOrganisasiArtikel bersama
Angga Riski Dwi SaputraState University of Semarang2
Grace Yudha SatriawanState University of Semarang2
Salsabila Rahadatul’ AisyState University of Semarang2
Erwin PrasetyoState University of Semarang1
Nafa FajriatiState University of Semarang1
Much Aziz MuslimState University of Semarang1
Jumanto JumantoState University of Semarang1
Rofik RofikState University of Semarang1
Endang SugihartiState University of Semarang1
Alamsyah AlamsyahState University of Semarang1
Riza ArifudinState University of Semarang1
Athifa Dihyan CalystaState University of Semarang1
Regina Ayumi UlayyaaState University of Semarang1
Barokah IsdaryantiState University of Semarang1
Isti HidayahState University of Semarang1
Lyna LatifahState University of Semarang1
FafuridaState University of Semarang1
Sabrina Desy RahmawatiState University of Semarang1
Kholiq BudimanState University of Semarang1
Fariska Ratna FauziahState University of Semarang1
Desi Adrianti AwaliyahState University of Semarang1
Rini MuzayanahState University of Semarang1
Apri Dwi LestariState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/jaist/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">Consumer Acceptance Analysis of Purchase Interest Using Live Features on The Marketplace with Technology Acceptance Model (TAM) Method Case Study : Shopee</dc:title>
	<dc:creator>Jhonatan, Edward</dc:creator>
	<dc:creator>Prasetiyo, Budi</dc:creator>
	<dc:description xml:lang="en-US">



The development of technology has become one of the instant lifestyles of the community because it has high mobility in carrying out daily activities. The use of the internet for commercial transactions is known as electronic commerce (e-Commerce). In 2021 Shopee launched a new feature before other competitors had the Shopee live feature. This research is more focused on analyzing buyers using the Shopee live feature on the Shopee marketplace using the Technology Acceptance Model (TAM). The purpose of this study is to analyze how the influence of consumers in buying interest using the Shopee live feature and to determine the effect of each variable used. This type of research is quantitative research. The research sample was 255 UNNES student respondents from 2015-2019. The data analysis method used is descriptive analysis using SEM with SmartPLS 3.0 software. The data that has been obtained is done data cleaning. It was found that the valid data were 203 people. The results of the research based on what has been done on the outer model, there are three indicators that are deleted, namely PEOU 2, PEOU 4, and PU 5, because the results obtained are still below the set value &amp;lt;0.7. In the inner model research, there is one hypothesis that is rejected, namely the t-statistics test, namely PEOU &amp;gt; BI because this hypothesis has a value less than the standard value of the t-test so it is rejected. However, there are six accepted hypotheses, namely PE &amp;gt; PU, PE &amp;gt; PEOU, PE &amp;gt; BI, PT &amp;gt; PU, PT &amp;gt; BI, and PU &amp;gt; BI. Based on the results of this analysis, the six variables have factors that influence the purchase intention using the Shopee live feature.



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	<dc:publisher xml:lang="en-US">Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2024-01-23</dc:date>
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	<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/jaist/article/view/61455</dc:identifier>
	<dc:identifier>10.15294/jaist.v5i2.61455</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Advances in Information Systems and Technology; Vol 5 No 2 (2023): October; 207 - 221</dc:source>
	<dc:source>2715-999X</dc:source>
	<dc:source>2714-9714</dc:source>
	<dc:source>10.15294/jaist.v5i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/jaist/article/view/61455/26318</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Journal of Advances in Information Systems and Technology</dc:rights>
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