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Workplace accidents resulting in Lost Time Injury (LTI) pose a serious challenge in maintaining occupational safety and operational efficiency, particularly in the logistics sector, which is known for its high level of risk. This study aims to analyze the causes of LTI-category workplace accidents in Group Company X in 2024 from the perspective of human factors using the Human Factors Analysis and Classification System (HFACS), which is based on the Swiss Cheese Model theory. A descriptive-analytic method with a qualitative approach was employed through the review of accident investigation reports and interviews with key persons. The findings reveal that the most significant contributing factors to LTI cases include, under latent conditions: organizational culture, planned inappropriate operations, physical environment, and tools/technology; while under active failures, the dominant factor is skill-based errors. Improvements in work systems, both at the organizational and individual levels, are necessary to create a safer and more sustainable work environment.
This research examines work-related accidents in the mining industry categorized as injury cases, using the Human Factors Analysis and Classification System in Mining Industry (HFACS-MI). The mining industry is known as a high-risk sector, where serious incidents such as major injuries and fatalities frequently occur despite investigations and preventive measures. The study aims to identify the main causal factors of workplace accidents based on the HFACS-MI framework, which classifies human errors and systemic weaknesses within mining organizations. Using data from injury-related accident cases in 2024, both qualitative and quantitative analyses were conducted to assess contributing factors from the operator level up to the organizational level.The findings reveal that the majority of accidents were triggered by unsafe acts, particularly skill-based errors, indicating deficiencies in workers' basic competencies. Additionally, latent failures, such as inadequate supervision and organizational inefficiencies, were also found to play a significant role.
Fire incidents are a prevalent type of work-related accident in the manufacturing sector, including the cement industry. PT X is one of the cement factories that reported 21 fire cases from 2020 to 2024, indicating a concerning trend of recurring incidents yearly. This study aims to analyze the fire trend at PT X through the lens of human factors, utilizing the Human Factors Analysis and Classification System (HFACS) approach. Employing a qualitative method with a descriptive-analytical design, the research relies on secondary data from the company's incident investigation reports and interviews with relevant stakeholders. This study performed data analysis to elucidate the characteristics and causal factors underlying the trend in fire incidents, utilizing the Human Factors Analysis and Classification System (HFACS) framework. The findings reveal that latent conditions significantly impact the fire trend more than active failures. Key causal factors identified in latent conditions include resource management, inadequate supervision, and crew resource management, while decision errors are the dominant causal factors identified in active failures.
Penelitian ini mengkaji kecelakaan kerja di industri pertambangan yang tergolong dalam kategori cedera, menggunakan metode Human Factors Analysis and Classification System in Mining Industry (HFACS-MI). Industri pertambangan dikenal sebagai sektor dengan risiko tinggi, di mana insiden besar seperti cedera kerja serius dan kematian sering kali terjadi meskipun telah dilakukan investigasi dan tindakan pencegahan.
Studi ini bertujuan untuk mengidentifikasi faktor-faktor penyebab utama kecelakaan berdasarkan pendekatan sistem HFACS-MI yang mengklasifikasikan kesalahan manusia dan kelemahan sistemik dalam organisasi tambang. Berdasarkan data kecelakaan kasus cedera Tahun 2024, analisis dilakukan secara kualitatif dan kuantitatif terhadap berbagai faktor, dari tingkat operator hingga organisasi.
Hasil penelitian mengungkapkan bahwa kecelakaan paling banyak dipicu oleh unsafe acts, terutama skill-based errors, yang menunjukkan kelemahan pada kompetensi atau keterampilan dasar pekerja. Selain itu, faktor latent failures seperti lemahnya supervisi dan ketidakefisienan sistem organisasi juga berperan penting.
This research examines work-related accidents in the mining industry categorized as injury cases, using the Human Factors Analysis and Classification System in Mining Industry (HFACS-MI). The mining industry is known as a high-risk sector, where serious incidents such as major injuries and fatalities frequently occur despite investigations and preventive measures. The study aims to identify the main causal factors of workplace accidents based on the HFACS-MI framework, which classifies human errors and systemic weaknesses within mining organizations. Using data from injury-related accident cases in 2024, both qualitative and quantitative analyses were conducted to assess contributing factors from the operator level up to the organizational level. The findings reveal that the majority of accidents were triggered by unsafe acts, particularly skill-based errors, indicating deficiencies in workers' basic competencies. Additionally, latent failures, such as inadequate supervision and organizational inefficiencies, were also found to play a significant role.
