Pendekatan Regresi Nonparametrik Kernel pada Data IHSG Periode Januari 2020 – Desember 2021

نویسندگان

چکیده

ABSTRAK
 Pendekatan regresi nonparametrik Kernel digunakan untuk memperkirakan harapan bersyarat dari variabel dependen terhadap independen tanpa mengasumsikan bentuk parametrik tertentu. ini menggunakan fungsi sebagai alat melakukan estimasi. Dalam penelitian ini, Gaussian dan estimator Nadaraya-Watson. Estimator Nadaraya-Watson adalah metode yang mengestimasi rata-rata tertimbang secara lokal, dengan pembobot. juga efektif dalam data memiliki pola runtun waktu, seperti indeks Dow Jones Indeks Harga Saham Gabungan (IHSG). Tujuan estimasi memprediksi IHSG dipengaruhi Jones. Model terbaik mempunyai bandwidth optimal ditentukan berdasarkan Generalized Cross Validation (GCV) minimum. Berdasarkan hasil diperoleh model nilai sebesar 0,332 GCV minimum 0,2455519. Hasil prediksi mengalami fluktuasi pada interval Rp6.100,00 sampai Rp6.400,00 terjadi bulan Maret 2021 hingga Desember 2021.
 ABSTRACT
 The nonparametric regression approach is used to estimate the conditional expectations of dependent variable on independent without assuming a particular parametric form. This uses function as tool for estimating. In this study, kernel and are used. method that estimates locally weighted average, using weight. also effective in estimating has time series pattern, such index Jakarta Composite Index (JCI). purpose study was predict JCI which influenced by variable. best one determined based (GCV). Based results research, obtained with value 0.332 0.2455519. prediction fluctuated at Rp. 6,100.00 6,400.00 occurred March December 2021.

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ژورنال

عنوان ژورنال: STATISTIKA: Journal of Theoretical Statistics and Its Applications

سال: 2023

ISSN: ['2599-2538', '1411-5891']

DOI: https://doi.org/10.29313/statistika.v23i1.1628