Open AccessImplementation of Ordinary Co-Kriging method for prediction of coal quality variable at unobserved locations
Author(s) -
Annisa Nur Falah,
Nor Aziati Abdul Hamid,
Endang Rusyaman,
Atje Setiawan Abdullah,
Budi Nurani Ruchjana
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1722/1/012076
Subject(s) - kriging , lagrange multiplier , estimator , variable (mathematics) , variance (accounting) , gaussian , mathematics , statistics , variables , mathematical optimization , mathematical analysis , physics , accounting , quantum mechanics , business
A Co-Kriging method is a method that used to predict the value of the point at unobserved locations by sample points are known to be spatially interconnected by adding other variables that have a correlation with the main variable or can also be used to predict 2 or more variables simultaneously. In this research, the Lagrange Multiplier approach is used to produce the minimum variance of the Co-Kriging estimator. The case study is predicted on coal quality variable, Fixed Carbon as the main variable with Calorific Value as an additional variable. The process of prediction calculation by Co-Kriging method using package GStat on R software which produces a best theoretical model is Gaussian model as input in the prediction calculation at unobserved locations. The calculation result with Lagrange Multiplier approach using R Program is faster, precise and accurate which produces minimum prediction variance for Fixed Carbon and Calorific Value variables.