Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.

This study focused on application of multiple regression in modeling vegetable oil prices. Five vegetable oil prices, namely CPO, SBO, CNO, PKO, and RSO have been analysed using monthly oil price data from year 2000. We found that multiple linear regression gave the $R^2$ value of 0.887, meaning 88....

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Main Authors: Khamis, Azme, Ismail, Zuhaimy, Shabri, Ani
Format: Article
Language:English
Published: Department of Mathematics, Faculty of Science 2003
Subjects:
Online Access:http://eprints.utm.my/8808/
http://eprints.utm.my/8808/1/ZuhaimyIsmail2003_PemodelanHargaMinyakSayuranMenggunakan.pdf
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author Khamis, Azme
Ismail, Zuhaimy
Shabri, Ani
author_facet Khamis, Azme
Ismail, Zuhaimy
Shabri, Ani
author_sort Khamis, Azme
building UTeM Institutional Repository
collection Online Access
description This study focused on application of multiple regression in modeling vegetable oil prices. Five vegetable oil prices, namely CPO, SBO, CNO, PKO, and RSO have been analysed using monthly oil price data from year 2000. We found that multiple linear regression gave the $R^2$ value of 0.887, meaning 88.7\% of variance in CPO price could be explained by RSO, PKO, and CNO. The $t$-test showed that the parameter estimates is significant at one percent level. This study concluded that multicollinearity and autocorrelation were detected inmuliple linear regression and are needed to be considered in further research.
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spelling utm-88082010-08-13T01:57:16Z http://eprints.utm.my/8808/ Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda. Khamis, Azme Ismail, Zuhaimy Shabri, Ani Q Science (General) QA Mathematics This study focused on application of multiple regression in modeling vegetable oil prices. Five vegetable oil prices, namely CPO, SBO, CNO, PKO, and RSO have been analysed using monthly oil price data from year 2000. We found that multiple linear regression gave the $R^2$ value of 0.887, meaning 88.7\% of variance in CPO price could be explained by RSO, PKO, and CNO. The $t$-test showed that the parameter estimates is significant at one percent level. This study concluded that multicollinearity and autocorrelation were detected inmuliple linear regression and are needed to be considered in further research. Department of Mathematics, Faculty of Science 2003-06 Article PeerReviewed application/pdf en http://eprints.utm.my/8808/1/ZuhaimyIsmail2003_PemodelanHargaMinyakSayuranMenggunakan.pdf Khamis, Azme and Ismail, Zuhaimy and Shabri, Ani (2003) Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda. Matematika, 19 (1). pp. 59-70. ISSN 0127-8274 http://www.fs.utm.my/matematika/content/view/79/31/
spellingShingle Q Science (General)
QA Mathematics
Khamis, Azme
Ismail, Zuhaimy
Shabri, Ani
Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title_full Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title_fullStr Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title_full_unstemmed Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title_short Pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
title_sort pemodelan harga minyak sayuran menggunakan analisis regresi linear berganda.
topic Q Science (General)
QA Mathematics
url http://eprints.utm.my/8808/
http://eprints.utm.my/8808/
http://eprints.utm.my/8808/1/ZuhaimyIsmail2003_PemodelanHargaMinyakSayuranMenggunakan.pdf