Multivariate Analysis of Limestone Petrography Data on Kalipucang Formation Using R

Abstract

Limestone may look physically and visually have the same characteristics but basically can be distinguished one of them with thin section rock analysis, this research to support petrography analysis of thin section rock data with a more quantitative approach using the method Principal component analysis and cluster analysis statistics to parse physical and visual characteristics. The study used 57 samples of thin section rock from three locations in a single rock formation, i.e. the location of Pancatengah-Tasikmalaya (PCT); Cijulang-Ciamis (CJL) and Sindangsari-Ciamis (SDS), analysed using open source software with replication R programming languages using packages: ggplot2; Dplyr; FactomineR; FactoExtra; Cluster and Ggcorrplot. The results of the study showed consistently the existence of three significant rock sampling classifications, i.e. one group showing the samples were in the area near the deposition with the main composition of foraminifera, algae, mud carbonate, coral fragments, Group 2 showed mixing with igneous rock with plagioclase composition, opaque, Glass, pyroxene and, Group 3 shows the rocks have been transported so that they are mixed with other sedimentary rocks having quartz compositions, iron oxides, rock fragments.