PERBANDINGAN METODE ANALISIS DISKRIMINAN, NEURAL NETWORK, DISKRIMINAN KERNEL, REGRESI LOGISTIC, MARS UNTUK DATA BANGKITAN (KOMBINASI VARIANS, OVERLAP DAN KORELASI)

Rinda Nariswari, Elok Fitriani Rafikasari

Abstract


Metode untuk pengklasifikasian data diantaranya menggunakan analisis diskriminan, analisis diskriminan kernel, analisis regresi logistik, neural network, dan MARS. Secara keseluruhan masing-masing metode jika diterapkan pada data mempunyai kelebihan maupun kekurangan. Pada pengelompokan data iris virginica dan vercicolor, metode MARS dan NN FeedForward paling baik digunakan. Sedangkan pada pengelompokan data iris setosa dan vercicolor, metode Analisis Diskriminan, NN RBF dan NN FeedForward adalah metode yang paling baik digunakan dalam pengelompokan. Namun berbeda dengan hasil analisis data simulasi yang dibangkitkan melalui Minitab, metode MARS adalah satu-satunya metode yang paling baik digunakan untuk data simulasi karena mempunyai rata-rata ketepatan klasifikasi yang paling besar diantara metode lainnya.


Keywords


Analisis Diskriminan, Analisis Diskriminan Kernel, Analisis Regresi Logistik, Neural Network, dan MARS.

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DOI: https://doi.org/10.33758/mbi.v13i11.273

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