Abstract:
Understanding household perceptions of water quality and safety is
essential for effective water management and public health planning. This study
analyses household water perception data from Sri Lanka’s Northern Province using
Association Rule Mining (ARM). Data from 101 households covering twelve categorical
perception variables were examined using the Apriori algorithm. Frequent itemsets
and association rules were evaluated using support, confidence, and lift measures.
The analysis identified consistent perception patterns, particularly linking perceived
water quality and supply reliability with household precautionary practices. Several
strong, high-confidence rules indicated non-random relationships among perception
variables. Overall, the findings demonstrate that ARM is a transparent and effective
method for uncovering latent perception structures in household survey data and
provides useful insights to inform water management and public health interventions.
