Assessment of Heavy Metal Contamination in Lake Toba Using Descriptive Statistics and Principal Component Analysis
Year: 2026
Type: article
Abstract: Eight monitoring stations were sampled in February 2026 in the Pangururan area of Lake Toba to evaluate heavy metal contamination under different anthropogenic influences.Heavy metal concentrations (cadmium (Cd), zinc (Zn), copper (Cu), mercury (Hg), iron (Fe), lead (Pb), and cyanide (CN⁻)) were determined using the Standard Methods of the American Public Health Association (APHA).Descriptive statistics, Pearson correlation analysis, and Principal Component Analysis (PCA) were employed to characterize spatial variation and identify the dominant variables influencing water quality.Water quality status was evaluated in accordance with the Indonesian Government Regulation No. 22 of 2021, under which monitoring stations exceeding the Fe standard were categorized as polluted.The results showed that Fe was the only parameter exceeding the applicable regulatory standard at several monitoring stations, whereas the remaining heavy metals remained below the corresponding threshold values.PCA identified Fe as the dominant variable contributing to spatial variability among the monitoring stations.Although supervised machine learning algorithms were initially explored during the analytical workflow, the limited dataset (n = 8 monitoring stations; L1 = 5 and L2 = 3) did not permit statistically reliable model evaluation.Therefore, the findings presented in this study are based primarily on descriptive statistics and multivariate analysis.These results provide baseline information for future large-scale and seasonal monitoring of heavy metal contamination in Lake Toba.
Institutions: Universitas Katolik Santo Thomas, Padjadjaran University
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204454041