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Faktor Exacta
Article . 2017
Data sources: DOAJ
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MODEL REGRESI PROBIT BIVARIAT

Authors: Nurfidah Dwitiyanti;

MODEL REGRESI PROBIT BIVARIAT

Abstract

Model regresi probit bivariat merupakan model regresi yang digunakan untuk menganalisis hubungan antara dua buah variabel respon yang berupa data kualitatif biner dengan satu atau lebih variabel prediktor. Variabel galat pada model ini diasumsikan berdistribusi normal bivariat. Metode kemungkinan maksimum dengan metode iterasi Newton Raphson digunakan untuk mendapatkan taksiran parameter regresi probit bivariat. Selanjutnya dilakukan pengujian signifikansi pada model ini dengan menggunakan uji perbandingan kemungkinan untuk menguji signifikansi parameter secara simultan dan uji Wald untuk menguji signifikansi parameter secara parsial. Uji Lagrange Multiplier digunakan untuk menguji ada atau tidaknya korelasi galat antara masing-masing variabel respon. Model probit bivariat diterapkan pada kasus kepercayaan seseorang (dalam hal ini responden) terhadap layanan internet yang dikaitkan dengan penggunaan internet serta faktor-faktor yang menentukan kemungkinan (peluang) seseorang percaya terhadap layanan internet dan penggunaan internet. Berdasarkan hasil analisis model probit bivariat diperoleh bahwa nilai peluang untuk setiap kepercayaan seorang responden terhadap layanan internet dan responden yang menggunakaan internet, secara bersama-sama (simultan) variabel prediktor yaitu pendidikan, pendapatan, usia, dan jenis kelamin mempunyai pengaruh terhadap peluang seorang responden yang percaya terhadap layanan internet dan responden yang menggunakan internet. 

Keywords

Technology, T

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold