LBS, Bivax Satria (2025) Efisiensi Penggunaan Alat Berat Pada Pekerjaan Lapisan Pekerasan Jalan Base A (Studi Kasus : Proyek Peningkatan Jalan Kecamatan Pangkalan Kerinci). Other thesis, Universitas Islam Riau.

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Abstract

The use of heavy equipment in Base A pavement construction plays a crucial role in improving project time‑ and cost‑efficiency. This research aims to compare the unit cost per cubic metre of material—calculated from field‑measured productivity of heavy equipment—with the corresponding unit prices listed in the project Bill of Quantity (BOQ). The study was conducted on the Road Improvement Project in Pangkalan Kerinci District using a time‑study approach to record cycle times of a wheel loader, dump truck, motor grader, and vibratory roller. The resulting costs were then evaluated to identify cost‑efficiency and highlight discrepancies between actual and planned conditions. A descriptive‑quantitative method was employed, with direct field observations of each equipment cycle: material loading by the wheel loader, hauling by the dump truck, grading by the motor grader, and compaction by the vibratory roller. Cycle durations were measured with a stopwatch and compared against BOQ productivity standards. Supporting variables—including terrain conditions, haul distance, fleet size, and waiting times—were also analysed for their impact on productivity. The analysis of heavy equipment productivity and efficiency in the implementation of Class A aggregate base course work shows significant variation among equipment types. The Motor Grader recorded the highest productivity at 537.02 m³/hour with a cost efficiency saving of 72.21%, followed by the Vibratory Roller with 335.04 m³/hour and a 77.74% cost reduction. In contrast, the Wheel Loader and Dump Truck showed lower performance with productivity levels of 89.00 m³/hour and 0.758 m³/hour, and operational cost increases of 31.83% and 32.06%, respectively. These differences highlight the importance of on-site monitoring and adaptive implementation strategies to optimize heavy equipment utilization in terms of both time and cost.

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