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The safety performance of a company shows how well the company is in protecting employee safety and reducing losses due to work accidents (Sullivan, 2000). Safety performance in a company or organization is influenced by various factors, one of which is the human factor. In the loss causation model, (Bird & Germain, 1996) explains that there are five elements as factors that cause accidents, namely lack of control due to inadequate programs, program standards and compliance with standards, basic causes consisting of personal factors and work factors, causes direct actions consisting of non-standard acts and conditions, and the resulting harm to people, property and processes. PT. X is a Mining Service Company engaged in blasting. From the data of safety accidents that occurred at PT. X over the past 10 years, it was found that 60% of the main causes of these accidents were due to the human factor. The research in this thesis aims to determine the effect of human factors on the safety performance of PT.X and to analyze the most influential human factors in improving the safety performance of PT. X as measured by the level of work accidents. Based on the loss causation model and the basic causes of work accidents at PT. X period 2009-2013, there were six (6) human factors studied, namely competence, fitness to work, compliance with procedures, safety communication, safety awareness, and safety behavior. The result of the research is that competence and communication are the most influential human factors in improving the safety of PT. X.
Pemerintah mendorong agar setiap perusahaan melakukan penerapan SMK3 di lingkungan kerja masing-masing. Sesuai dengan Peraturan Pemerintah Republik Indonesia Nomor 50 Tahun 2012. Penerapan K3 sering kali dianggap sebagai cost atau beban biaya bagi perusahaan, bukan investasi untuk mencegah kecelakaan kerja. Menurut data organisasi perburuhan internasional (ILO) sekitar 2,78 juta pekerja meninggal setiap tahun karena kecelakaan kerja dan penyakit akibat kerja. Penelitian bertujuan untuk menganalisis kesesuaian Kinerja SMK3 dan tingkat pemahaman budaya keselamatan karyawan di Perusahaan X. Data Penelitian meliputi data primer dengen FGD menggunakan kuisioner safety culture maturity The Hudson Model dalam 6 kelompok Jabatan dan data sekunder (hasil temuan eksternal audit ISO 45001 : 2018 dan SMK3 sesuai PP No. 50 tahun 2012). Metodelogi penelitian menggunakan deskriptif analitik dan mix metode (semi kuantitatif dan kualitatif). Ada 20 variabel metode Hudson diperoleh tingkat kematangan budaya pada angka 3,33 (kategori Kalkulatif). Ini berarti keselamatan dianggap sebagai tanggung jawab Petugas K3 atau unit K3 saja yang berfokus terhadap pemenuhan standar atau peraturan saja yang menjadi minimum requirement. Tingkat pengukuran kinerja SMK3 perusahaan telah berada di level memuaskan menunjukan bahwa hasil SMK3 Perusahaan mengkonfirmasi apa yang dideteksi tingkat kematangan budaya keselamatan Perusahaan baru mulai untuk pemenuhan standar K3 dan kebutuhan peraturan perundang-undang. Perusahaan belum melakukan improvement ke arah generative yang sesungguhnya untuk menuju level proaktif dan generative tidak bisa hanya berfokus pada kebutuhan SMK3 namun banyak hal yang dibutuhkan improvement. Jika Perusahaan ingin menuju tingkat proaktif keselamatan dan nilai tingkat budaya generative maka keselamatan harus menjadi nilai yang diyakini secara bersama di seluruh organsasi dan unit kerja.
The government encourages every company to implement SMK3 in their respective work environments. In accordance with Republic of Indonesia Government Regulation Number 50 of 2012. Implementing K3 is often considered a cost or burden for companies, not an investment to prevent work accidents. According to data from the International Labor Organization (ILO), around 2.78 million workers die every year due to work accidents and occupational diseases. The research aims to analyze the suitability of SMK3 performance and the level of understanding of employee safety culture at Company in accordance with PP No. 50 of 2012). The research methodology uses analytical descriptive and mixed methods (semi quantitative and qualitative). There are 20 variables in the Hudson method, the level of cultural maturity is 3.33 (Calculative category). This means that safety is considered the responsibility of the K3 Officer or K3 unit which focuses on fulfilling standards or regulations which are the minimum requirements. The level of measurement of the company's SMK3 performance has been at a satisfactory level, indicating that the Company's SMK3 results confirm what was detected. The maturity level of the company's safety culture is just starting to fulfill K3 standards and statutory regulatory requirements. The company has not made improvements in a truly generative direction. In order to reach a proactive and generative level, it cannot only focus on SMK3 needs, but there are many things that need improvement. If the Company wants to move towards a proactive level of safety and a generative cultural value level, then safety must become a value that is shared across the organization and work units. Key words: Conformity, Safety Performance, Safety Culture Maturity Level
Kecelakaan tambang di Indonesia menunjukkan beban yang perlu dikendalikan secara sistemik, melalui efektivitas pengukuran awal Safety Maturity Level (SML). Penelitian ini bertujuan menganalisis hubungan antara SML dan kinerja keselamatan pertambangan yaitu indikator kecelakaan (Frequency Rate dan Severity Rate), sekaligus menjelaskan faktor konteks yang memengaruhi kekuatan hubungan tersebut. Penelitian menggunakan desain mixed methods - explanatory sequential. Fase kuantitatif memanfaatkan data sekunder dari Kementerian ESDM (KESDM) tahun 2024 di 52 perusahaan tambang batubara tahap operasi produksi sesuai kriteria inklusi, yaitu skor SML berbasis KepDirjen Minerba nomor 10.K/MB.01/DJB.T/2023 dan data statistik kecelakaan tambang 2024. Uji normalitas data menunjukkan tidak terdistribusi normal, sehingga analisis menggunakan pendekatan nonparametrik Spearman rho (ρ) dan GLM gamma. Hasil kuantitatif mengindikasikan bahwa SML secara total (agregat) berkorelasi negatif dan signifikan dengan kinerja keselamatan (indeks kecelakaan tambang), namun kontribusi tiap dimensi SML tidak seragam. “Upaya Pengendalian” merupakan indikator yang paling konsisten bersifat protektif terhadap indeks kecelakaan, sedangkan “Partisipasi Pekerja” tidak menunjukkan hubungan yang signifikan namun korelasi negatif; sementara itu, “Tanggung Jawab Pimpinan” dan “Analisis Statistik”
menunjukkan hubungan negatif (bivariat) dan positif (multivariat), serta signifikan terhadap indeks kecelakaan tambang. Selanjutnya, temuan kualitatif dari data sekunder KESDM terhadap sub-sampling perusahaan menegaskan bahwa SML tinggi tidak selalu diikuti penurunan kecelakaan ketika terdapat kesenjangan implementasi pengendalian, terutama pada tata kelola kontraktor, kompetensi, dan konsistensi eksekusi di lapangan. Penelitian menyimpulkan bahwa SML berdampak pada penurunan kecelakaan terutama jika diwujudkan dalam pengendalian risiko yang nyata dan pembelajaran berbasis data yang ditutup dengan tindakan (closed-loop learning), bukan sekadar pemenuhan administratif.
Mining accidents in Indonesia indicate a burden that must be controlled systemically through the effectiveness of early measurement of the Safety Maturity Level (SML). This study aims to analysis the relationship between SML and mining safety performance represented by accident indicators (Frequency Rate and Severity Rate) while also explaining contextual factors that influence the strength of this relationship. The research employs a mixed-methods design with an explanatory sequential approach. The quantitative phase utilizes secondary data from the Ministry of Energy and Mineral Resources (KESDM) for 2024, covering 52 coal mining companies at the production operation stage that met the inclusion criteria, namely SML scores based on the Director General of Mineral and Coal Decree No. 10.K/MB.01/DJB.T/2023 and 2024 mine accident statistics. Data normality tests showed non-normal distributions; therefore, analysis was conducted using nonparametric Spearman’s rho (ρ) and a gamma Generalized Linear Model (GLM). Quantitative results indicate that overall (aggregate) SML is negatively and significantly correlated with safety performance (the mining accident index), but the contribution of each SML dimension is not uniform. “Control Measures” emerged as the most consistently protective indicator against the accident index, whereas “Worker Participation” showed no significant relationship, although the correlation direction was negative. Meanwhile, “Leadership Responsibility” and “Statistical Analysis” demonstrated negative (bivariate) and positive (multivariate) relationships, and both were significant with respect to the mining accident index. Furthermore, qualitative findings derived from secondary KESDM data on a subsample of companies confirm that a high SML does not always translate into reduced accidents when gaps in the implementation of controls persist—particularly in contractor governance, competency, and consistency of execution in the field. This study concludes that SML contributes to accident reduction primarily when it is translated into tangible risk controls and data-driven learning that is closed with corrective action (closed-loop learning), rather than merely fulfilling administrative requirements.