Jurnal Gaussian
Vol 7, No 3 (2018): Jurnal Gaussian

PEMODELAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI SPLINE MULTIVARIABEL

Ihdayani Banun Afa (Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro)
Suparti Suparti (Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro)
Rita Rahmawati (Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro)



Article Info

Publish Date
29 Aug 2018

Abstract

The Composite Stock Price Index (CSPI) is a composite index of all types of shares listed on the stock exchange and their movements indicate the conditions occurring in the stock market. CSPI movement is an important indicator for investors to determine whether they will sell, hold, or buy a stock. One of the factors that influence the movement of CSPI is Inflation (X1), Exchange Rate (X2) and SBI rate (X3). This study aims to obtain the best CSPI model using a multivariable nonparametric spline regression approach. The approach is done by nonparametric regression because the regression curve obtained does not show a certain relationship pattern. Spline is very dependent on the order and location of the knot point. The best spline model is the model that has the minimum MSE (Mean Square Error) value. In this study, the best spline regression model is when X1 is 4 order, X2 is 2 order and X3 is 2 order. The number of knots on X1 is 1 knot at 8.22, X2 is 2 knots at 13066.82 and 13781.75 While X3 is 2 knots at 6.6 and 6.67 with value of MSE equal to 6686.85.Keywords: Composite Stock Price Index, Multivariable Spline Regression, MSE

Copyrights © 2018






Journal Info

Abbrev

gaussian

Publisher

Subject

Other

Description

Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM ...