BibTex Citation Data :
@article{Medstat19991, author = {Ihdayani Afa and Suparti Suparti and Rita Rahmawati}, title = {PERBANDINGAN METODE REGRESI LINIER MULTIVARIABEL DAN REGRESI SPLINE MULTIVARIABEL DALAM PEMODELAN INDEKS HARGA SAHAM GABUNGAN}, journal = {MEDIA STATISTIKA}, volume = {11}, number = {2}, year = {2018}, keywords = {}, abstract = { The composite stock price index or Indonesia Composite Index (ICI) is a composite index of all stocks listed on the Indonesia Stock Exchange and its movements indicate conditions that occur in the capital market. For investors, the ICI movement is one of the important indicator to make a decision whether the stocks will be sold, held or bought new shares. The ICI movement (y) was influenced by several factors including Inflation (x 1 ), Exchange Rate (x 2 ) and SBI interest rate (x 3 ). This study aims to compare the ICI modeling using the parameric and nonparametric approaches, namely multivariable linear regression and multivariable spline regression. Determination of the better model is based on the smaller MSE and the larger R 2 . The best regression model is multivariable spline regression with x 1 , x 2 and x 3 , each with a sequence orde (3,2,2) and the number of knot points (1,2,2). Keywords: Indonesia Composite Index, Multiple Linear Regression, Multivariable Spline Regression, MSE, R 2 }, issn = {2477-0647}, pages = {147--158} doi = {10.14710/medstat.11.2.147-158}, url = {https://ejournal.undip.ac.id/index.php/media_statistika/article/view/19991} }
Refworks Citation Data :
The composite stock price index or Indonesia Composite Index (ICI) is a composite index of all stocks listed on the Indonesia Stock Exchange and its movements indicate conditions that occur in the capital market. For investors, the ICI movement is one of the important indicator to make a decision whether the stocks will be sold, held or bought new shares. The ICI movement (y) was influenced by several factors including Inflation (x1), Exchange Rate (x2) and SBI interest rate (x3). This study aims to compare the ICI modeling using the parameric and nonparametric approaches, namely multivariable linear regression and multivariable spline regression. Determination of the better model is based on the smaller MSE and the larger R2. The best regression model is multivariable spline regression with x1, x2 and x3, each with a sequence orde (3,2,2) and the number of knot points (1,2,2).
Keywords: Indonesia Composite Index, Multiple Linear Regression, Multivariable Spline Regression, MSE, R2
Article Metrics:
Last update:
Last update: 2024-04-19 03:43:12
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Media Statistika journal and Department of Statistics, Universitas Diponegoro as the publisher of the journal. Copyright encompasses the rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Media Statistika journal and Department of Statistics, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Media Statistika journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form Media Statistika]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Dr. Di Asih I Maruddani (Editor-in-Chief) Editorial Office of Media StatistikaDepartment of Statistics, Universitas DiponegoroJl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275Telp./Fax: +62-24-7474754Email: maruddani@live.undip.ac.id
Media Statistika
Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro
Gedung F Lantai 3, Jalan Prof Jacub Rais, Kampus Tembalang
Semarang 50275
Visitor Number:
Indexing:
