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Ndaru Dian Darmawanti
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PEMODELAN INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS) Ndaru Dian Darmawanti; Suparti Suparti; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (533.391 KB) | DOI: 10.14710/j.gauss.v3i4.8088

Abstract

Composite Stock Price Index (CSPI) is a historical information about the movement of joint-stock until a certain date. CSPI is often used by inventors to see a representation of the overall stock price, it can analyze the possibility of increase or decrease in stock price. Following old examination, some economy macro variables affecting CSPI is inflation, interest rate,and exchange rate the Rupiah againts the u.s.dollar. MARS method is particularly suitable to analyze a CSPI because many variables that affected. Furthermore, in the real world is very difficult to find a spesific data pattern. The analysis is MARS analysis. The purpose is an obtained a MARS model to be used to analyze the CSPI movement’s. Selection MARS model can be used CV method. The MARS model is an obtained from combination of BF, MI, dan MO. In this case, happens the best models with BF=9, MI=2, dan MO=1. Accuracy for MARS model can see MAPE values is 14,32588% it means the model can be used.Keyword: CSPI, economy macro, MARS, CV, MAPE.
Co-Authors Diah Safitri Suparti Suparti