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Laili Isna Nur Khiqmah
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PERBANDINGAN DISKRIMINAN KUADRATIK KLASIK DAN DISKRIMINAN KUADRATIK ROBUST PADA KASUS PENGKLASIFIKASIAN PEMINATAN PESERTA DIDIK (Studi Kasus di SMA Negeri 1 Kendal Tahun Ajaran 2014/2015) Laili Isna Nur Khiqmah; Moch. Abdul Mukid; Alan Prahutama
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.665 KB) | DOI: 10.14710/j.gauss.v4i2.8577

Abstract

Discriminant is a multivariate statistical technique that can be used to perform the classification new observation into a particular group. Quadratic discriminant analysis tied to an assumption of normal multivariate distributed observations and variance covariance matrix inequality. Robust quadratic discriminant analysis can be used if the observations contain outliers. Classification using robust quadratic discriminant analysis with the Minimum Covariance Determinant (MCD) estimator in the data specialization students of SMA Negeri 1 Kendal that containing outliers gives the results of the classification accuracy of 95,06% with a percentage of 4,94% classification error while generating the classical quadratic discriminant analysis classification accuracy of 92,59% with a percentage of 7,41% classification error. Thus a robust quadratic discriminant analysis with the MCD estimator is more appropriate in the case of the data which contains outliers. Keywords : discriminant, outliers, robust, MCD  estimators, classification
Co-Authors Alan Prahutama Moch. Abdul Mukid