📅 10 July 2026
DOI: 10.26877/asset.v8i3.3616
Prediction of Ground Vibration due to Blasting Activities of Coal Open Pit Mine Near Village Residents Using Multivariate Logarithmic Regression
Advance Sustainable Science, Engineering and Technology (ASSET)
Universitas Persatuan Guru Republik Indonesia Semarang
📄 Abstract
Blasting activities are among the most important in mining and can have a negative impact on the environment and surrounding communities, causing disruption and even damaging nearby buildings and infrastructure. If the community protests and demonstrates, mining operations may be shut down, which would be very detrimental to the company. Studies are needed on effective planning to reduce the negative impacts. Ground vibrations measured by Peak Particle Velocity (PPV) are subject to thresholds set by each region's standards; in this research area, the maximum threshold is 3 mm/s to avoid damage to nearby buildings or settlements. The important variables are the explosive charge per delay and the distance, along with other blasting geometry variables such as spacing, burden, stemming, powder factor, and number of blast holes. Several previous researchers have used methods to predict PPV, with detonation parameters as the independent variables. This research uses general empirical methods and multivariate logarithmic regression (MLR). Prediction using MLR is better than general empirical methods; with R2 = 0.925, RMSE = 0.247, MAE = 0.548, MAPE = 0.218, and VAF = 96.66%, indicating near-perfect prediction. The MLR model produces a reference maximum explosive charge per delay of 59.09 kg.
🔖 Keywords
#ground vibrations; blasting; peak particle velocity; multivariate logarithmic regression
ℹ️ Informasi Publikasi
Tanggal Publikasi
10 July 2026
Volume / Nomor / Tahun
Tahun 2026
📝 HOW TO CITE
Prasmoro, Alloysius Vendhi; Siswanto, Nurhadi; Santosa, Budi ; Nugraha, Giri Waluyo ; Salleh , Mohd Shukor , "Prediction of Ground Vibration due to Blasting Activities of Coal Open Pit Mine Near Village Residents Using Multivariate Logarithmic Regression," Advance Sustainable Science, Engineering and Technology (ASSET), Jul. 2026.
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