Multifactorial Analysis of Work Accidents among Transportation Sector Workers in Parepare City

Russeng, Syamsiar S.; Saleh, Lalu Muhammad; Syafitri, Nurul Mawaddah; Imran, Naufal Hilmy; Nurazizah, Auliya; Nurhidayah, Andi Fatimah Mustovia

doi:10.30597/mkmi.v19i4.31186

Akses terbuka Jurnal

Multifactorial Analysis of Work Accidents among Transportation Sector Workers in Parepare City

Media Kesehatan Masyarakat Indonesia · Vol. 19 No. 4 (2023) · hlm. 169–174

DOI: 10.30597/mkmi.v19i4.31186
ISSN: 2356-4067, 0216-2482
Terbit: 2023-12-31
Penerbit: Faculty of Public Health, Hasanuddin University, Makassar
Bahasa: en
Lisensi: creativecommons.org/licenses/by-nc-sa/4.0/

Abstrak

Reports have shown that there has been a continuous annual increase in the number of traffic accidents in Indonesia. Parepare City, in particular, faces significant congestion in its public transportation system, leading to 167 cases and 144 cases of accidents in 2019 and 2020, respectively. Therefore, this study aims to analyze the influence of knowledge, attitude, personality, and safety riding practice on traffic accidents among transportation workers in Parepare City. This cross-sectional study comprised 100 respondents selected using the simple random sampling method. The study instrument was a questionnaire, which had previously been tested for its validity and reliability. The data obtained were analyzed using univariate analysis to describe the characteristics of each variable. In contrast, bivariate analysis was conducted using the chi-square test with a confidence level of 95%. Data were collected through interviews with a questionnaire and analyzed using multiple logistic regression with the forward LR method. The results showed that attitude and safety riding practice had a significant influence. Multivariate analysis showed that factors influencing accidents included attitude (AOR = 0.031; 95%CI = 0.45-0.26), practice (AOR = 0.108; 95%CI = 0.03-0.38), and knowledge (AOR = 0.337; 95%CI = 0.13-0.88), while personality had no effect. Based on the results, future studies were advised to conduct long-term investigations (longitudinal studies) to monitor changes in the variables observed and the relationship with the rate of traffic accidents.

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Hasanuddin University
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Rekan penulis	Organisasi	Artikel bersama
Istiana Tadjuddin	Hasanuddin University	3
Iva Hardi Yanti	Hasanuddin University	3
Yulianah Rahmadani	Hasanuddin University	3
Mahfuddin Yusbud	Hasanuddin University	3
Dimi Cindyastira	Afiliasi tidak diketahui	1
Andi Wahyuni	Afiliasi tidak diketahui	1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/mkmi/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en">Multifactorial Analysis of Work Accidents among Transportation Sector Workers in Parepare City</dc:title>
	<dc:creator xml:lang="en">Russeng, Syamsiar S.</dc:creator>
	<dc:creator xml:lang="en">Saleh, Lalu Muhammad</dc:creator>
	<dc:creator xml:lang="en">Syafitri, Nurul Mawaddah</dc:creator>
	<dc:creator xml:lang="en">Imran, Naufal Hilmy </dc:creator>
	<dc:creator xml:lang="en">Nurazizah, Auliya</dc:creator>
	<dc:creator xml:lang="en">Nurhidayah, Andi Fatimah Mustovia</dc:creator>
	<dc:subject xml:lang="en">Knowledge</dc:subject>
	<dc:subject xml:lang="en">attitude</dc:subject>
	<dc:subject xml:lang="en">behavior</dc:subject>
	<dc:subject xml:lang="en">accidents</dc:subject>
	<dc:subject xml:lang="en">safety riding</dc:subject>
	<dc:description xml:lang="en">Reports have shown that there has been a continuous annual increase in the number of traffic accidents in Indonesia. Parepare City, in particular, faces significant congestion in its public transportation system, leading to 167 cases and 144 cases of accidents in 2019 and 2020, respectively. Therefore, this study aims to analyze the influence of knowledge, attitude, personality, and safety riding practice on traffic accidents among transportation workers in Parepare City. This cross-sectional study comprised 100 respondents selected using the simple random sampling method. The study instrument was a questionnaire, which had previously been tested for its validity and reliability. The data obtained were analyzed using univariate analysis to describe the characteristics of each variable. In contrast, bivariate analysis was conducted using the chi-square test with a confidence level of 95%. Data were collected through interviews with a questionnaire and analyzed using multiple logistic regression with the forward LR method. The results showed that attitude and safety riding practice had a significant influence. Multivariate analysis showed that factors influencing accidents included attitude (AOR = 0.031; 95%CI = 0.45-0.26), practice (AOR = 0.108; 95%CI = 0.03-0.38), and knowledge (AOR = 0.337; 95%CI = 0.13-0.88), while personality had no effect. Based on the results, future studies were advised to conduct long-term investigations (longitudinal studies) to monitor changes in the variables observed and the relationship with the rate of traffic accidents.</dc:description>
	<dc:publisher xml:lang="en">Faculty of Public Health, Hasanuddin University, Makassar</dc:publisher>
	<dc:date>2023-12-31</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://journal.unhas.ac.id/index.php/mkmi/article/view/31186</dc:identifier>
	<dc:identifier>10.30597/mkmi.v19i4.31186</dc:identifier>
	<dc:source xml:lang="en">Media Kesehatan Masyarakat Indonesia; Vol. 19 No. 4: DECEMBER 2023; 169-174</dc:source>
	<dc:source>2356-4067</dc:source>
	<dc:source>0216-2482</dc:source>
	<dc:source>10.30597/mkmi.v19i4</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/mkmi/article/view/31186/11074</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 by author</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-nc-sa/4.0/</dc:rights>
</oai_dc:dc>