PERBANDINGAN METODE KUADRAT TERKECIL DAN METODE BAYES PADA MODEL REGRESI LINIER BERGANDA YANG MENGANDUNG MULTIKOLINIEIRITAS

Authors

  • Siska Auqino
  • Maiyastri Maiyastri
  • Rita Diana

DOI:

https://doi.org/10.25077/jmu.8.1.307-312.2019

Abstract

Penelitian ini bertujuan untuk mengkaji perbandingan Metode Kuadrat Terkecil (MKT) dan metode Bayes pada model regresi linier berganda yang mengandung multikolinieritas. Pada regresi linier berganda, asumsi yang sering tidak terpenuhi yaitu tidak ada multikolinieritas di antara variabel prediktor. Adanya multikolinieritas menyebabkan estimasi MKT menjadi tidak efisien. Oleh karena itu diperlukan metode alternatif yang menghasilkan kesalahan estimasi yang lebih kecil. Data yang digunakan adalah data random dengan dua variabel prediktor yang dibangkitkan sehingga data memenuhi sifat model yang diteliti. Penelitian ini menunjukkan bahwa metode Bayes lebih baik dalam mengestimasi parameter regresi linier berganda dilihat dari nilai Mean Squared Error (MSE) yang lebih kecil dibandingkan dengan MKT.

Diterima: Direvisi: Dipublikasikan :

Kata Kunci: Metode Kuadrat Terkecil, Metode Bayes, Multikolinieritas

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Published

05-07-2019

Issue

Vol. 8 No. 1 (2019)

Section

Articles

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