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All Journal Media Statistika Jurnal Gaussian
Suparti Suparti
Departemen Statistika, Universitas Diponegoro
Decision Sciences, Operations Research & Management Other

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PERBANDINGAN METODE REGRESI LINIER MULTIVARIABEL DAN REGRESI SPLINE MULTIVARIABEL DALAM PEMODELAN INDEKS HARGA SAHAM GABUNGAN Ihdayani Banun Afa; Suparti Suparti; Rita Rahmawati
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.648 KB) | DOI: 10.14710/medstat.11.2.147-158

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 (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
PERAMALAN INDEKS JAKARTA ISLAMIC INDEX (JII) DENGAN PENDEKATAN REGRESI PARAMETRIK LINIER SEDERHANA DAN REGRESI NONPARAMETRIK KERNEL DILENGKAPI GUI R-SHINY Rahmadia Fitri; Suparti Suparti; Puspita Kartikasari
Jurnal Gaussian Vol 12, No 2 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.2.221-230

Abstract

Investment in Islamic stocks in Indonesia has increased from 2019 to 2021. One of the references for investors in monitoring Islamic stock price movements is the Jakarta Islamic Index_(JII).  The_purpose_of_this_research_is_to model the index (JII) using nonparametric kernel regression.  The kernel_functions_used_in nonparametric regression are Gaussian, Uniform, Triangle, and Epanechnikov._The research data-is-divided-into-In-Sample-data-for the period January-2010-to-December 2020 and-Out-Sample-data.for the_period_January_2021_to_December_2021. The_best_model_is selected based_on_the smallest MSE-value-obtained by the Triangle kernel regression with an optimum bandwidth (h) of 48,  2.  The R2 value is 0.897.  Based on the criteria for the R2 value, it-can-be-stated that_the_best model_is_a strong model_with a proportion of_the influence-of-the-previous index-on-the.current index value of-89.7%, and-there-maining_10.3%_is_influenced_by_other_factors.-The best model forecasting ability can be seen from the MAPE data out sample value of 3.04%, which is less than 10%, meaning that the performance of the kernel model in predicting the JII index is very good.  This research uses R software which is equipped with R-Shiny GUI to help with data processing.
Co-Authors Ihdayani Banun Afa Puspita Kartikasari Rahmadia Fitri Rita Rahmawati