BibTex Citation Data :
@article{J.Gauss36596, author = {Rahmadia Fitri and Suparti Suparti and Puspita Kartikasari}, title = {PERAMALAN INDEKS JAKARTA ISLAMIC INDEX (JII) DENGAN PENDEKATAN REGRESI PARAMETRIK LINIER SEDERHANA DAN REGRESI NONPARAMETRIK KERNEL DILENGKAPI GUI R-SHINY}, journal = {Jurnal Gaussian}, volume = {12}, number = {2}, year = {2023}, keywords = {JII, Regression; ARIMA; Nonparametric; Kernel; MSE; GUI}, 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 R 2 value is 0.897. Based on the criteria for the R 2 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. }, issn = {2339-2541}, pages = {221--230} doi = {10.14710/j.gauss.12.2.221-230}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/36596} }
Refworks Citation Data :
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.
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