(IGEOS UPI 2017) Multivariate Analysis of Limestone Petrography Data onKalipucang Formation Using R

Achmad Darul^1,#., Dasapta Erwin Irawan²., Jejen Ramdani¹., Fauzan Septiana¹., Siti Saniyyah Sholihat³

Research location: geological map of Karangnunggal (Supriatna, et al 1992)

Abstrak. Limestone is one of the most strategic construction materials. Its physical properties are controlled by chemical properties. Different types of limestone can be distinguished by examining thin section. However, it is still complicated to classify limestones based on qualitative observation. Geologists also need a method to classify a large number of samples based on training data. This paper applies multivariate statistical techniques (principal component analysis and cluster analysis) to assist sample classification. We used 57 samples of thin section rock of Kalipucang Formation from three location: Pancatengah-Tasikmalaya (PCT); Cijulang-Ciamis (CJL) and Sindangsari-Ciamis (SDS). An open source R statistical package was used in the analysis. The result from our training data shows a consistent classification with the initial visual classification. Each location shows distinct petrographical compositions: Group 1 shows the dominant control of depositional environment with strong values of foraminifera, algae, mud carbonate, coral fragments. Group 2 shows a mixing with igneous rock with plagioclase, opaque, glass, pyroxene. Group 3 shows the mixing with transported-sediment with traces of quartz compositions, iron oxides, rock fragments. However, we need to make more trials using more data set to test this method.

 Key word: Limestones, Multivariate analysis, Petrography.