Manajemen Kelelahan Berbasis Teknologi di Industri Pertambangan: Dampaknya Terhadap Keselamatan dan Produktivitas Operasional Dump Truck

Millenia, Tasya (2025) Manajemen Kelelahan Berbasis Teknologi di Industri Pertambangan: Dampaknya Terhadap Keselamatan dan Produktivitas Operasional Dump Truck. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kelelahan operator alat berat merupakan salah satu penyebab penurunan keselamatan dan produktivitas di industri pertambangan. Penelitian ini menganalisis efektivitas manajemen kelelahan berbasis teknologi melalui penerapan Fatigue Alertness System (FAS) dan Fleet Management System (FMS) pada operasi dump truck di PT XYZ. Metode yang digunakan adalah mixed method, yaitu analisis data historikal FAS dan FMS periode 2021–2024, serta kuesioner dan wawancara untuk menggali persepsi operator dan manajemen. Hasil analisis menunjukkan bahwa moderate fatigue dan shift malam berpengaruh signifikan terhadap peningkatan kecepatan, mengindikasikan pola compensatory behavior yang berpotensi meningkatkan risiko insiden. Pola temporal menunjukkan jam rawan kelelahan pada 12.00–15.00 (siang) dan 21.00–24.00 hingga akhir shift malam. Implementasi FAS berkontribusi terhadap penurunan fatigue event hingga 79% dan delay operasi sebesar 75%, serta meningkatkan budaya keselamatan. Meskipun demikian, tantangan terkait akurasi alarm masih memerlukan penguatan edukasi dan kalibrasi sistem. Penelitian ini menegaskan bahwa teknologi deteksi kelelahan dapat meningkatkan keselamatan dan produktivitas apabila didukung kebijakan operasional yang tepat. Rekomendasi mencakup peningkatan akurasi deteksi, optimasi SOP intervensi, serta pengembangan model monitoring kelelahan fisik dan mental
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Heavy equipment operator fatigue is one of the causes of decreased safety and productivity in the mining industry. This study analyzes the effectiveness of technology-based fatigue management through the implementation of the Fatigue Alertness System (FAS) and Fleet Management System (FMS) in dump truck operations at PT XYZ. A mixed method approach was used, including analysis of historical FAS and FMS data for the 2021–2024 period, along with questionnaires and interviews to explore operator and management perceptions. The analysis results show that moderate fatigue and night shifts significantly influence speed increases, indicating compensatory behavior patterns that potentially increase the risk of incidents. Temporal patterns indicate fatigue-prone hours between 12:00–15:00 (noon) and 21:00–24:00 until the end of the night shift. FAS implementation contributed to a 79% reduction in fatigue events and a 75% reduction in operational delays, as well as an improved safety culture. However, challenges related to alarm accuracy still require strengthening education and system calibration. This study confirms that fatigue detection technology can improve safety and productivity when supported by appropriate operational policies. Recommendations include improving detection accuracy, optimizing intervention SOPs, and developing physical and mental fatigue monitoring models.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	manajemen kelelahan, Fatigue Alertness System, Fleet Management System, produktivitas dump truck, fatigue management, dump truck productivity.
Subjects:	T Technology > T Technology (General) > T58.8 Productivity. Efficiency T Technology > TN Mining engineering. Metallurgy > TN341 Mine haulage.
Divisions:	61101-Magister Management Technology
Depositing User:	Tasya Millenia
Date Deposited:	06 Jan 2026 06:37
Last Modified:	06 Jan 2026 06:37
URI:	http://repository.its.ac.id/id/eprint/129290

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