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Puspita Kartikasari
Departemen Statistika, Universitas Diponegoro

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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.