PENENTUAN UKURAN CONTOH DAN REPLIKASI BOOTSTRAP UNTUK MENDUGA MODEL REGRESI LINIER SEDERHANA

Authors

  • Olivia Atinri
  • Hazmira Yozza
  • Yudiantri Asdi

DOI:

https://doi.org/10.25077/jmu.3.2.53-61.2014

Abstract

Analisis regresi adalah suatu teknik statistika yang digunakan untuk menarik
suatu kesimpulan mengenai hubungan antara satu variabel tak bebas ( Y) dengan satu
atau lebih variabel bebas ( X) dalam suatu sistem. Dalam analisis regresi, diperlukan
beberapa asumsi yang harus dipenuhi oleh sebaran komponen galat (ε). Metode bootstrap merupakan salah satu metode yang dapat digunakan untuk menduga nilai-nilai
penduga parameter jika asumsi sebaran komponen galat tidak terpenuhi. Dalam metode
bootstrap biasanya dilakukan resampling sebanyak B kali ulangan bootstrap. Penelitian
ini menggunakan metode simulasi Monte Carlo. Penelitian ini dilakukan dengan tujuan
menentukan banyaknya ulangan bootstrap untuk menduga β0 dan β1 pada analisis regresi linier sederhana. Hasil dari penelitian ini diperoleh, untuk ulangan bootstrap B=5
menghasilkan nilai ragam penduga bootstrap relatif lebih tinggi. Untuk ukuran contoh
berukuran lebih atau sama dari 40, tidak perlu dilakukan banyak ulangan bootstrap,
karena dengan melakukan ulangan yang sedikit penduga parameter regresi sederhana
sudah memiliki ragam yang kecil. Untuk sampel berukuran yang lebih kecil, dapat dilakukan 25 kali ulangan bootstrap. Namun perlu dicatat untuk ukuran sampel sebesar
10 sebaiknya tidak digunakan, karena menghasilkan penduga parameter regresi dengan
ragam yang masih cukup besar.

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Published

01-06-2016

How to Cite

Atinri, O., Yozza, H., & Asdi, Y. (2016). PENENTUAN UKURAN CONTOH DAN REPLIKASI BOOTSTRAP UNTUK MENDUGA MODEL REGRESI LINIER SEDERHANA. Jurnal Matematika UNAND, 3(2), 53–61. https://doi.org/10.25077/jmu.3.2.53-61.2014

Issue

Vol. 3 No. 2 (2014)

Section

Articles

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