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In the industrial era 4.0 and technological developments, all industrial sectors are required to ensure that their companies have a concept of system resilience from all kinds of potential for variability in business processes, which is then referred to as the concept of resilience. This study aims to analyze the application of the concept of safety resilience in mining industry companies to determine the level of the company's ability to deal with unexpected conditions. The design of this research study is descriptive with a semi-quantitative method and uses the Resilience Assessment Grid (RAG) tools as an interview guide. Data were collected by reviewing company documents and conducting interviews using the purposive sampling technique. Based on the results of the analysis, PT X has an element of resilience by comparing the company's reliability with the amount of risk. In addition, the level of implementation of the safety resilience concept at PT X has an average percentage of 87.9% which is included in the stage towards resilience with details on response-ability (88.9%), monitoring ability (89.2%), learning ability (86.1%), and anticipation (87.6%). The technological approach, good response-ability, and commitment from company officials are aspects that support the high level of implementation of the safety resilience concept at PT X. Meanwhile, the imbalance in the level of risk perception among workers and the company's learning base that still prioritizes the safety-I paradigm is an obstacle for companies to implement maximum safety resilience concept.
Human Factors Analysis and Classification System in Mining Industry (HFACS-MI) is an accident investigation method to find the factors that cause accidents in the mining industry. The HFACS method itself has been widely used for accident investigations in various industries such as aviation, construction, railroads, and other industries. This method consists of 5 (five) levels, namely unsafe act, precondition for unsafe act, unsafe leadership, organizational influences, and outside factors. PT. XYZ is a mining company in the East Kalimantan region. Accidents that have occurred certainly make the company suffer losses, it is necessary to study the analytical process in detail to find out the active and latent causal factors and find out the interrelationships of the causes of accidents from various levels using the HFACS-MI method.
Industri pertambangan merupakan kegiatan industri yang mempunyai risiko tinggi. Faktor manusia telah diidentifikasi sebagai penyebab paling umum terjadinya kecelakaan besar di industri pertambangan. Oleh karena itu, penelitian ini bertujuan menganalisis data kecelakaan di PT. X dengan menggunakan kerangka analisis faktor manusia dan sistem klasifikasi industri pertambangan (HFACS-MI). Metode penelitian ini melibatkan pengumpulan data kualitatif untuk 322 kasus kecelakaan di PT. X yang terjadi pada tahun 2018-2022 dari basis data Sistem Manajemen Insiden yang dikategorikan sebagai cedera yang dapat dicatat. Faktor penyebab kecelakaan ini diberi kode menggunakan kerangka HFACS-MI. Data kecelakaan dianalisis menggunakan statistik deskriptif. Temuan penelitian menunjukkan bahwa 84% dari seluruh kecelakaan melibatkan pekerja kontraktor dan 16% melibatkan pekerja tetap PT. X. Hasil analisis menggunakan kerangka HFACS-MI menunjukkan bahwa setiap lapisan atau tingkatan memberikan kontribusi terhadap kecelakaan, yaitu faktor luar (44%), pengaruh organisasi (68%), kepemimpinan tidak aman (90%), prasyarat tindakan tidak aman (99%), dan tindakan tidak aman (99,7%). Temuan ini menekankan perlunya fokus pada pengurangan jumlah kesalahan manusia selama operasi penambangan untuk mengurangi tren kecelakaan saat ini. Kerangka kerja HFACS-MI telah terbukti menjadi alat penting untuk analisis kecelakaan yang kuat terhadap faktor manusia di pertambangan.
The mining industry is an industrial activity with high risks. Human factors have been identified as the most common cause of major accidents in the mining industry. Therefore, this research aims to analyze accident data at PT. X using the human factors analysis and classification system-mining industry framework (HFACS-MI). This research collected qualitative data for 322 accident cases at PT. X occurring from 2018 to 2022 from the Incident Management System database categorized as recordable injuries. Factors causing the accidents were coded using HFACS-MI framework. Accident data were analyzed using descriptive statistics. The study findings revealed that 84% of all accidents involved contractor workers and 16% involved the PT. X permanent workers. The results of analysis using the HFACS-MI framework show that each layer or level contributes to accidents, namely outside factors (44%), organizational influences (68%), unsafe leadership (90%), preconditions of unsafe acts (99%), and unsafe acts (99.7%). These findings emphasize the need to focus on reducing the number of human errors during mining operations to reduce the current accident trend. The HFACS-MI framework has proven to be a valuable tool for robust accident analysis of human factors in mining.
