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Working at heights is a high-risk activity. Falls from heights accounted for 38% of the 105,182 work accidents in the construction sector. In 2020 and 2021, PT.X had two falls from a height. Organizational influence is the biggest contributor in both cases. This study discusses in depth the analysis of work accidents at the height that occurred at PT.X in 2020-2021 using human factors aspects. In the accident analysis, one of the theories of human factors will be used, namely the Swiss Cheese Model with derivative tools, namely Human Factors Analysis and Classification. The research method used is a case study using secondary data and interviews with PT.X. The use of human factors aspects in accidents at work will find latent conditions and active failures that can be contributing factors to accidents. Latent conditions found include lack of management awareness in enforcing safety aspects, unavailability of optimal safety support facilities, and others. While active conditions that contribute include lack of knowledge and training of workers about hazards and controls in the workplace, violation of work rules, and others. Researchers suggest PT.X make improvements to the factors that contribute to the incidence of accidents, especially at the management and organizational levels.
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.
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.
Kata kunci:Kecelakaan, analisis kecelakaan, Human Factors And Classification System, HFACS, Comprehensive List Of Causes, CLC
This thesis assess the accident in PT XYZ 2015 by using Human Factors AndClassification System (HFACS) framework. This research is a semi-quantitativewith design study analytical descriptive. Results from this study are a layer ofHFACS most weakness is unsafe act at 11 from total 11 accidents with theelements of decision error becomes a factor of the number one weakness, thenfollowed with a precondition of unsafe act at 10 with the elements of conditions ofservice to be the factors that most contribute to accidents, followed by unsafesupervision at 7 with inadequate leadership element is the factor that mostcontributed to the accident, and the latter as much as 5 of organizationalinfluences with elements of organizational climate and resource management isthe factor that most contributed to the accident. The analysis of research suggestscorrective actions at each level of HFACS, not only for active failures but alsolatent failures with reinforcing corrective action at the unsafe act layer.
Key words:Accident, accident analysis, Human Factors And Classification System, HFACS,Comprehensive List Of Causes, CLC
Occupational accident cases in the cement industry, especially the packer area, are a serious problem that can have an impact on many things including productivity, safety, and worker welfare. Data shows that occupational accidents in the Packer area of the PT X Cement Industry in 2024 have increased compared to 2023, making it the area with the highest accident frequency in 2024. Occupational accident investigations and corrective actions have been conducted, but accidents continue to recur. This may be due to the absence of human factor analysis during the investigation process. Therefore, this study was conducted to determine contribution of human factors specifically latent conditions and active failures to occupational accidents that occurred in the PT X packer area during 2023-2024. This study was conducted using a descriptive analytical method using the Human Factor Analysis Classification System (HFACS) method. The results of the study showed that latent conditions contributed more to occupational accidents than active failures. The latent condition factors that contributed the most to occupational accidents included organizational climate, organizational process, resource management, and inadequate supervision. Meanwhile, the active failure factor that contributed the most was decision error. PT X needs to improve latent conditions at the organizational level and implement control to mitigate active failures in the packer area.
