Water Quality Assessment and Characterization of Rivers in Pasir Gudang, Johor via Multivariate Statistical Techniques

In Pasir Gudang, an accelerated industry-based economy has caused a tremendous increase and diversity of water contamination. The application multivariate statistical techniques can identify factors that influence systems is valuable tool for managing resources. Therefore, this study presents spatial evaluation the elucidation inordinate complex data 32 parameters from 25 sampling points spanning 20 rivers across summing up to 1500 observations between 2015-2019. Hierarchical cluster analysis with K-means method grouped into two main clusters, i.e., proportionately low polluted Cluster 1 (C1) high 2 (C2), based on similitude quality profiles. discriminant applied resulted in reduction 7 (Cl, Cd, S, OG, temperature, BOD, pH) 99.5% correct categorization analysis. Hence, element complexity was reduced few criteria accountable large differences C1 C2. principal component produced 6 components after rotation C2, respectively, where total variance 62.48% 66.85%. addition, several sub-clusters were identified; three contributing components. These results show functionality be effectively used characteristics pollution sources. outcomes may benefit legislators within Gudang.