Estimasi Sumberdaya untuk Data dengan Distribusi Lognormal pada Endapan Urat Emas Gunung Pongkor dengan Pendekatan Geostatistik

Penulis

  • Idris Herkan Afandi Fakultas Teknik Pertambangan dan Perminyakan, Institut Teknologi Bandung
  • M. Nur Heriawan Fakultas Teknik Pertambangan dan Perminyakan, Institut Teknologi Bandung

Kata Kunci:

Geostatisic, Lognorma Distribution, Logmormal Kriging

Abstrak

This study aims to determine the method of estimation and data processing are suitable to the lognormal distribution data. Data obtained from the assay data of gold vein mineralization from Gunung Pongkor, West Java. Data provided are relatively only a few or not proportionate to the volume of mineral bodies, range of space (average 50 m to the north), as well as lognormal distribution data. Data collection was enlarged by conducting composites within 1 m, resulting in 828 points. Furthermmineral, the data is divided into the data without a top cut and the data with a top cut, for the benefit to estimate data also has been transformated into logarithm. Variogram modeling performed on each data to get a geostatistical parameters. The estimation method that used are methods such as of Ordinary Kriging (OK), Lognormal Ordinary Kriging (OLK) and Sichel's t-estimator. The criteria used suitably is the correlation coefficient value estimation results with actual levels valued mmineral than 0.6. Assumptions for the best method is the method that has the best accuracy between the regression line with line bisector and for the method that has a variance estimation is a method which has an average smallest variance estimation. The cumulative distribution curve estimation results show the difference in the results of the estimates using the data without a top cut and the data with a top cut. This research resulted in the values of the correlation coefficient from the three methods are mmineral than 0.6. The most appropriate regression line with a line bisektor is Lognormal Ordinary Kriging method (OLK) both use the data without a top cut and the data with a top cut and the average of smallest variance estimation is a method of Ordinary Kriging (OK) that use data with the top cut.

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2018-03-30