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The following paper is a try out on the application of multivariate analysis (regression tree, principal component analysis, and cluster analysis) for classifying hot water chemistry. The number of sample analysed was 416 from all over Indonesia. Regression tree technique has failed to read the data structure due to multi-collinearity effect therefore PCA and cluster analysis were applied. We used open source R statistical packages to do the calculation. Such technique classifies hot water samples into three major clusters: cluster 1 (pure hot water), cluster 2 (mixing water), and cluster 3 (cold-meteoric water). Similar clustering were also detected in the PCA plot. The statistical is able to detect the close and open geothermal system based on data structure. This robust method should be applied to more geothermal system with larger dataset to see its performance.

Excerpt from main dissertation

Excerpt from main dissertation

Excerpt from main dissertation

Bungee, Spring

Flaschenzug, pulley

Classe do LaTeX para manuscritos da Escola Politécnica da USP. A classe poliTeX (leia-se "POLITEK") é baseada na classe para monografias ABNT adaptada pelo Prof. Paulo Barreto para os padrões da POLI-USP. Modelo de acordo com a norma POLI 2013 Repositório original: https://github.com/lchamon/poliTeX

Template for the journal of Electronic Letters on Computer Vision and Image Analysis (ELCVIA).