Operasi pertambangan nikel PT X memiliki risiko keselamatan tinggi yang melibatkan alat berat (heavy equipment) seperti dump truck. Sepanjang periode 2023–2025, terjadi tren peningkatan kecelakaan yang signifikan di area IUP dan jalan angkut utama (main hauling road), meningkat dari 39 insiden pada 2023 menjadi 95 insiden pada 2025, termasuk kejadian Loss Time Injury (LTI) dan fatalitas. Karena program keselamatan yang ada belum menurunkan angka kecelakaan secara signifikan , diperlukan kajian akademis terstruktur untuk mengevaluasi interaksi berbagai faktor penyebab insiden. Tujuan Penelitian ini adalah untuk menganalisis hubungan dan interaksi antara faktor manusia, organisasi, dan teknologi terhadap risiko kecelakaan kerja heavy equipment di PT X tahun 2026 sebagai dasar perumusan mitigasi risiko di industri nikel. Kerangka konsep menggunakan The Egg Agregated Model (TEAM). Penelitian ini merupakan kuantitatif deskriptif analitik menggunakan desain cross-sectional untuk uji bivariat menggunakan chi-square dan regresi logistik untuk uji multivariat. Penelitian dilakukan pada April - Mei 2026 di Sulawesi Tenggara. Dari populasi 532 operator dump truck, diambil sampel 229 responden secara simple random sampling. Data primer dikumpulkan melalui kuesioner daring berbasis skala Likert yang telah dinyatakan valid dan reliabel. Analisis multivariat menggunakan regresi logistik binary dengan metode Backward Manual (alpha = 5%). Hasil Penelitian: Sebanyak 60,3% operator berada pada kategori berisiko buruk. Uji regresi logistik binary model final menghasilkan 7 variabel yang berhubungan secara signifikan dan independen terhadap risiko kecelakaan kerja heavy equipment, diurutkan berdasarkan kekuatan pengaruh (Odds Ratio/OR) dan kontribusi Beta: Sikap terhadap Keselamatan (OR = 9,378; β = 23,81%); Kepercayaan pada Organisasi (OR = 5,589; β = 18,31%); Prosedur (OR = 3,611; β = 13,66%); Pengetahuan (OR = 3,177; β = 12,30%); Metode & Aplikasi Verifikasi (OR = 2,730; β = 10,68%); Perilaku Pekerja terhadap Teknologi (OR = 2,718; β = 10,64%); Komitmen Manajemen (OR = 2,710; β = 10,61%). Variabel karakteristik pribadi, kepemimpinan, keterampilan/kemampuan, pelatihan, dan komunikasi keselamatan tidak signifikan pada model akhir (p > 0,05$). Dari keseluruhan sistem yang memengaruhi risiko kecelakaan heavy equipment, faktor manusia memberikan kontribusi (36,11%), diikuti faktor teknologi (34,98%), dan faktor organisasi (28,92%). Faktor manusia merupakan skala prioritas utama yang harus dilakukan intervensinya. Meskipun demikian, teori menegaskan bahwa ketiga faktor (manusia, organisasi, dan teknologi) memiliki hubungan timbal-balik (reciprocal), bukan linear atau searah. Oleh karena itu, perbaikan tidak boleh berfokus pada perubahan faktor manusia saja melainkan harus menyentuh ketiga faktor tersebut secara bersamaan.

PT X’s nickel mining operations involve high safety risks associated with heavy equipment such as dump trucks. Throughout the 2023–2025 period, there was a significant upward trend in accidents within the IUP area and on the main hauling road, rising from 39 incidents in 2023 to 95 incidents in 2025, including Lost Time Injuries (LTIs) and fatalities. Since existing safety programs have not significantly reduced accident rates, a structured academic study is needed to evaluate the interactions among various factors contributing to these incidents. The objective of this study is to analyze the relationships and interactions between human, organizational, and technological factors regarding the risk of heavy equipment workplace accidents at PT X in 2026 as a basis for formulating risk mitigation strategies in the nickel industry. The conceptual framework employs The Egg Aggregated Model (TEAM). This study is a descriptive-analytical quantitative study using a cross-sectional design for bivariate tests via the chi-square test and logistic regression for multivariate tests. The study was conducted from April to May 2026 in Southeast Sulawesi. From a population of 532 dump truck operators, a sample of 229 respondents was selected using simple random sampling. Primary data were collected via an online questionnaire based on a Likert scale that had been validated and found to be reliable. Multivariate analysis was performed using binary logistic regression with the Backward Manual method (alpha = 5%). Research Results: A total of 60.3% of operators fell into the high-risk category. The binary logistic regression test of the final model identified 7 variables that were significantly and independently associated with the risk of heavy equipment workplace accidents, ranked by strength of influence (Odds Ratio/OR) and Beta contribution: Attitude toward Safety (OR = 9.378; β = 23.81%); Trust in the Organization (OR = 5.589; β = 18.31%); Procedures (OR = 3.611; β = 13.66%); Knowledge (OR = 3.177; β = 12.30%); Verification Methods & Applications (OR = 2.730; β = 10.68%); Worker Attitudes Toward Technology (OR = 2.718; β = 10.64%); Management Commitment (OR = 2.710; β = 10.61%). The variables of personal characteristics, leadership, skills/abilities, training, and safety communication were not significant in the final model (p > 0.05). Of all the systems influencing the risk of heavy equipment accidents, human factors contributed the most (36.11%), followed by technological factors (34.98%), and organizational factors (28.92%). Human factors are the top priority for intervention. However, theory asserts that the three factors—human, organizational, and technological—have a reciprocal relationship, not a linear or one-way one. Therefore, improvements should not focus solely on changes to human factors but must address all three factors simultaneously.