Abstract
The capital market is one of the economic drivers and representations for assessing the condition of companies in a country. Indonesia Stock Exchange (IDX) as one of the institutions in the capital market has 24 types of indexes that can be used as main indicators that reflect the performance of capital market, two of them are the Composite Stock Price Index (CSPI) and the Jakarta Islamic Index (JII). CSPI and JII movements are influenced by several factors, both from domestic and from foreign, such as inflation and the Dow Jones Industrial Average (DJIA). Modeling of CSPI and JII in this study was carried out using biresponses spline truncated nonparametric regression methods using Graphical User Interface (GUI) R with the intention of facilitating the analysis process. This method is used because there is a correlation between CSPI and JII and there is no specific relationship pattern between the response variable (CSPI and JII) and the predictor variable (inflation and DJIA). The best biresponses spline truncated model is determined by the order, number and location of the knots seen based on minimum GCV criteria. By using monthly data from January 2016 to December 2019, the best biresponses spline truncated model is obtained when the model for CSPI is in order 2 and the model for JII is in order 3 with 2 knots for each predictor variable. This model has a coefficient of determination of 85,54437% and MAPE of 2,65595% so that it has a very good ability in forecasting.
Highlights
Pasar modal merupakan salah satu penggerak perekonomian dan representasi untuk menilai kondisi perusahaanperusahaan di suatu negara
Data dalam penelitian ini dibagi menjadi dua, yaitu data in sample yang digunakan dalam pembentukan model dengan periode data bulanan terhitung sejak Januari 2016 sampai dengan Desember 2018 dan data out sample yang digunakan untuk peramalan dengan periode data bulanan terhitung sejak
Jurnal Ekonomi dan Kebijakan Publik Indonesia Vol 4, No 1: Hal. 35-48
Summary
Titik knot merupakan titik perpaduan bersama yang memperlihatkan terjadinya perubahan perilaku fungsi spline pada interval-interval yang berbeda [1]. Untuk mendapatkan spline optimal perlu dipilih banyaknya titik knot yang optimal. Salah satu metode yang paling banyak dipakai dan disukai karena kelebihan yang dimilikinya adalah metode GCV (Generalized Cross Validation). Validation (CV), metode GCV mempunyai sifat optimal asimtotik [13].
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