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Distribution, Severity, and Root Causes of Traffic Accidents in a Logistics Company

Jurnal Kesehatan Masyarakat · Vol. 21 No. 4 (2026) · pp. 884–893

DOI
10.15294/kemas.v21i4.40248
ISSN
2355-3596, 1858-1196
Published
2026-07-09
Publisher
Universitas Negeri Semarang in collaboration with Ikatan Ahli Kesehatan Masyarakat Indonesia (IAKMI Tingkat Pusat) and Jejaring Nasional Pendidikan Kesehatan (JNPK)
Language
eng

Abstract

Traffic accidents are the main issue in logistics and transportation, causing health and economic losses, including lowering productivity. The study aimed: 1) to investigate the distribution of accidents, 2) to examine the category and severity of accidents based on operational type, and 3) to evaluate the root cause of accidents in logistics/goods transportation. This quantitative study was conducted in Indonesia using the data from Logistics Corporation from 2022 to 2023. The variable consists of operational type, accident category, severity, and root cause. This study was analysed using descriptive and inferential statistics. The chi-square was used to examine the statistical test, with the alpha set at 5%. The analysis was performed in Stata Ver 13 (College Station, TX, USA). A total of 288 accidents were reported during 2022-2023, with the accidents being highly distributed on Java (50%) and Sumatra (44.79%). The Accident category noted that collisions with objects, hits, and single-vehicle accidents are prevalent. The accident severity is as follows: minor severity (83.33%) and higher minor severity (16.67%). The statistical test also exhibits a significant on accident severity between last mile and long haul (p value < 0.05). According to operational type, long-haul operations have high accident intensity, while last-mile operations have severe accidents. The root cause of the accident is caused by third-party error (32.98%), followed by driver behavior (30.56%), driver competence (13.88%), and driver distraction (6.59%). The company should establish regulations, standard operating procedures (SOPs), work shift schedules, and vehicle maintenance protocols, and ensure their implementation. Additionally, measuring stress levels and work-related fatigue among drivers should be conducted to help prevent accidents.

Keywords

Collaboration network of the authors

40 authors · 88 co-authorship links · showing the 40 most connected

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  • Universitas Jambi
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Yemima Sahmura VividiaAffiliation unknown2
Roro AzizahAffiliation unknown2
Arih Puspita MurtiAffiliation unknown2
Annisa Fitria NurdiansariAffiliation unknown2
Revalina Putri JuliyantiAffiliation unknown2
Annastya KinasihAffiliation unknown2
Lutfi ArdiantiAffiliation unknown1
Ari SujiptoAffiliation unknown1
M Thahir HaningAffiliation unknown1
Ashlikhatul Fuadah Al HasyimAffiliation unknown1
Dwi Sarwani Sri` RejekiAffiliation unknown1
Rachmat PermadiAffiliation unknown1
Sisworo SisworoAffiliation unknown1
Syahru RomadhoniAffiliation unknown1
Moh NasutionAffiliation unknown1
Dewi EllianaAffiliation unknown1
Ana Dwi TamaraAffiliation unknown1
Lia Ainun NikmahAffiliation unknown1
Priyanto PriyantoUniversitas Jambi1
Mohammad Kamal FauziAffiliation unknown1
Revi ErawatiAffiliation unknown1
Fitri Awalia PutriAffiliation unknown1
Annisah AnnisahAffiliation unknown1
Waliyudin WaliyudinAffiliation unknown1
Setyono Yudo TyasmoroAffiliation unknown1
Rahmah Dewi YustikaAffiliation unknown1
I Putu SriarthaAffiliation unknown1
Sri Rum GiyarsihAffiliation unknown1
Emi SukiyahAffiliation unknown1
Edi Tri HaryantoAffiliation unknown1
Pradnya Paramarta Raditya RendraAffiliation unknown1
Hendarmawan HendarmawanAffiliation unknown1
Herlan DarmawanAffiliation unknown1
Bachtiar Wahyu MutaqinAffiliation unknown1
Wahyudi WahyudiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/kemas/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">Distribution, Severity, and Root Causes of Traffic Accidents in a Logistics Company</dc:title>
	<dc:creator xml:lang="en">Hamidya, Syifa Ula</dc:creator>
	<dc:creator xml:lang="en">Rizaldi, Muhammad Addin</dc:creator>
	<dc:creator xml:lang="en">Suratman, Suratman</dc:creator>
	<dc:creator xml:lang="en">Ali, Khaidar</dc:creator>
	<dc:creator xml:lang="en">Ulfah, Nur</dc:creator>
	<dc:subject xml:lang="en">Accident</dc:subject>
	<dc:subject xml:lang="en">Saverity</dc:subject>
	<dc:subject xml:lang="en">Logistics and Transportation</dc:subject>
	<dc:subject xml:lang="en">Root Cause</dc:subject>
	<dc:description xml:lang="en">Traffic accidents are the main issue in logistics and transportation, causing health and economic losses, including lowering productivity. The study aimed: 1) to investigate the distribution of accidents, 2) to examine the category and severity of accidents based on operational type, and 3) to evaluate the root cause of accidents in logistics/goods transportation. This quantitative study was conducted in Indonesia using the data from Logistics Corporation from 2022 to 2023. The variable consists of operational type, accident category, severity, and root cause. This study was analysed using descriptive and inferential statistics. The chi-square was used to examine the statistical test, with the alpha set at 5%. The analysis was performed in Stata Ver 13 (College Station, TX, USA). A total of 288 accidents were reported during 2022-2023, with the accidents being highly distributed on Java (50%) and Sumatra (44.79%). The Accident category noted that collisions with objects, hits, and single-vehicle accidents are prevalent. The accident severity is as follows: minor severity (83.33%) and higher minor severity (16.67%). The statistical test also exhibits a significant on accident severity between last mile and long haul (p value &amp;lt; 0.05). According to operational type, long-haul operations have high accident intensity, while last-mile operations have severe accidents. The root cause of the accident is caused by third-party error (32.98%), followed by driver behavior (30.56%), driver competence (13.88%), and driver distraction (6.59%). The company should establish regulations, standard operating procedures (SOPs), work shift schedules, and vehicle maintenance protocols, and ensure their implementation. Additionally, measuring stress levels and work-related fatigue among drivers should be conducted to help prevent accidents.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang in collaboration with Ikatan Ahli Kesehatan Masyarakat Indonesia (IAKMI Tingkat Pusat) and Jejaring Nasional Pendidikan Kesehatan (JNPK)</dc:publisher>
	<dc:date>2026-07-09</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.unnes.ac.id/journals/kemas/article/view/40248</dc:identifier>
	<dc:identifier>10.15294/kemas.v21i4.40248</dc:identifier>
	<dc:source xml:lang="en">Jurnal Kesehatan Masyarakat; Vol. 21 No. 4 (2026); 884-893</dc:source>
	<dc:source>2355-3596</dc:source>
	<dc:source>1858-1196</dc:source>
	<dc:source>10.15294/kemas.v21i4</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/kemas/article/view/40248/10548</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2026 Jurnal Kesehatan Masyarakat</dc:rights>
</oai_dc:dc>