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ANALISIS INDEKS HARGA SAHAM GABUNGAN DAN FAKTOR PENGARUHNYA MENGGUNAKAN PEMODELAN REGRESI SEMIPARAMETRIK KERNEL DILENGKAPI GUI-R

*Arnisa Melani Kahar  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Suparti Suparti  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Arief Rachman Hakim  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2023 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Composite Stock Price Index (IDX) shows the movement of stock prices used by investors to determine their investment strategy. IDX movement is influenced by macroeconomic factors such as money supply and inflation, so regression analysis is used to determine the relationship between the variables. Based on the scatterplot, money supply is known as a parametric predictor variable as it has a linier line patterned scatterplot and inflation is a nonparametric predictor variable as it has a random patterned scatterplot, so semiparametric regression modelling is used for the analysis. Kernel regression was chosen to analyze the nonparametric component based on the random patterned scatterplot of inflation. This study aims to obtain the results of semiparametric kernel regression modelling analysis and to create a GUI to be applied to the analysis as a development of previous similar studies that still done based on CLI. This study uses monthly data from January 2013 to December 2020 with the proportion of in sample and out sample data distribution 87,5%:12,5%. Based on the smallest MSE value as the best model criteria, semiparametric regression model with triangle kernel function is the best model obtained with optimal bandwidth=3.24,  which means the model is strong and  which means that the forecasting results are very accurate. GUI has been created according to the needs of the modelling analysis implementation.

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Keywords: IDX; Money Supply; Inflation; Kernel Semiparametric Regression; MSE; R^2; MAPE; GUI.

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  1. Blanchard, O. 2006. Macroeconomics 4th Edition. New Jersey : Pearson Prentice Hall
  2. Carmona, R.A. 2004. Statistical Analysis of Financial Data in S-PLUS. New York : Springer-Verlag
  3. Chin, W.W. 1998. The Partial Least Squares Approach to Structural Equation Modeling. Modern Methods for Business Research : Hal. 295-336
  4. Fitriani, A., Srinadi, I.G.A.M., dan Susilawati, M. 2015. Estimasi Model Regresi Semiparametrik Menggunakan Estimator Kernel Uniform (Studi Kasus : Pasien DBD di RS Puri Raharja). E-Jurnal Matematika Vol. 4 No. 4 : Hal. 176-180
  5. Gujarati, D. 2003. Basic Econometrics. New York : Mc-Grawhill
  6. Hardle, W. 1994. Applied Nonparametric Regression. Berlin : Humboldt University
  7. Hardle, W., Liang, H., dan Gao, J. 2000. Partially Linear Models. Heidelberg : Physica-Verlag
  8. Kurniasih, D., Mariani, S., dan Sugiman. 2013. Efisiensi Relatif Estimator Fungsi Kernel Gaussian Terhadap Estimator Polinomial Dalam Peramalan USD Terhadap JPY. Unnes Journal of Mathematics Vol. 2 No. 2 : Hal. 79-84
  9. Lewis, C.D. 1982. International and Business Forecasting Methods. London : Butterworths
  10. Makridakis, S.G., Wheelwright, S.C., dan Hyndman, R.J. 1997. Forecasting : Methods and Applications. New York : John Wiley & Sons
  11. Nanda, D.A., Suparti, dan Hoyyi, A. 2016. Analisis Pengaruh Jumlah Uang Beredar dan Nilai Tukar Rupiah Terhadap Indeks Harga Saham Gabungan Menggunakan Pemodelan Regresi Semiparametrik Kernel. Jurnal Gaussian Vol. 5 No. 3 : Hal. 373-382
  12. Perdina, N.P. 2012. Pendugaan Model Regresi Semiparametrik Menggunakan Penduga Kernel. Bali : Universitas Udayana
  13. Sukirno, S. 2002. Pengantar Teori Makroekonomi Edisi Kedua. Jakarta : PT Raja Grafindo Persada
  14. Sunariyah. 2003. Pengantar Pengetahuan Pasar Modal. Jakarta : Erlangga
  15. Suparti, Santoso, R., Prahutama, A., dan Devi, A.R. 2018. Regresi Nonparametrik. Ponorogo : Wade Group
  16. Wand, M.P. dan Jones, M.C. 1995. Kernel Smoothing. New York : Chapman & Hall

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