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All Journal Pendidikan Geografi Jurnal Sains Matematika dan Statistika Desimal: Jurnal Matematika al-Afkar, Journal For Islamic Studies INSIST (International Series on Interdisciplinary Research) JATI (Jurnal Mahasiswa Teknik Informatika) JURNAL PENDIDIKAN DASAR FLOBAMORATA MATHunesa: Jurnal Ilmiah Matematika Jurnal Siger Matematika Jurnal Dedikasi untuk Negeri Jurnal Teknologi Pangan dan Ilmu Pertanian Sciencestatistics: Journal of Statistics, Probability, and Its Application
Eri Setiawan
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : Jurnal Siger Matematika

 1 
Analisis Regresi Komponen Utama Robust dengan Metode Minimum Covariance Determinant – Least Trimmed Square (MCD-LTS) Siska Diah Ayu Larasati; Khoirin Nisa; Eri Setiawan
Jurnal Siger Matematika Vol 1, No 1 (2020): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.312 KB) | DOI: 10.23960/jsm.v1i1.2472

Abstract

Principal Component Regression (PCR) is a method used to overcome multicollinearity problems by reducing the dimensions of independent variables to obtain new simpler variables without losing most of the information contained in the  variables. If the data analyzed contain outliers, a robust method on PCR is required. In this paper we use a robust method which is a combination of Robust Principal Component Analysis using the Minimum Covariance Determinant (MCD) method and Robust Regression Analysis using Least Trimmed Square (LTS) method. The purpose of this study is to examine the robust PCR analysis using the MCD-LTS method and to know the robustness of the method by looking at its sensitivity to outliers. For this purpose  we compared the MCD-LTS PCR  to the classic PCR based on the bias and Mean Square Error (MSE) values on several different sample sizes and percentages of outliers. The results of this study indicate that robust PCR using MCD-LTS is effective and efficient in overcoming the problem of multicollinearity and outliers in regression analysis. 
Model EGARCH dan TGARCH untuk Mengukur Volatilitas Asimetris Return Saham Sofalina Nodra Brilliantya; Khoirin Nisa; Subian Saidi; Eri Setiawan
Jurnal Siger Matematika Vol 3, No 2 (2022): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v3i2.3111

Abstract

Model Generalized Autoregressive Conditional Heterocedasticity (GARCH) merupakan salah satu pemodelan data deret waktu yang digunakan untuk mengukur data yang memiliki varians residual yang tidak konstan atau bersifat heteroskedastisitas.  Heteroskedastisitas terjadi karena data deret waktu memiliki volatilitas yang tinggi.  Model Exponential GARCH (EGARCH) dan Threshold GARCH (TGARCH) adalah model-model GARCH yang dapat mengatasi efek asimetris pada volatilitas.  Data yang digunakan pada penelitian ini adalah data return saham harian PT KB Bukopin Tbk (BBKP).  Penelitan ini bertujuan untuk menerapkan model EGARCH dan TGARCH serta mendapatkan  model terbaik dalam mengukur volatilitas asimetris data return saham harian.  Pemilihan model terbaik didasarkan pada nilai Akaike Information Criterion (AIC) terkecil.  Hasil analisis menunjukan bahwa model EGARCH (2,1) adalah model terbaik untuk mengukur dan meramalkan volatilitas asimetris return saham yang digunakan.
Co-Authors Aang Nuryaman Abdul Munip Alma Primasasti, Gabriella Claudia Amanabella, Maulina Amanathi, Ani Anandatara, Reza ansyah, Aldi Aqzela, Araneta Arini, Faras Nur D. Yadi Heryadi Darina, Novi Dona Setia Umbara Fitriani, Debi Nur Fridayanto, Syahlan Naufal Ika Kartika Indyah Hartami Santi Khoirin Nisa Maghfiroh, Hani Muhammad Luthfi Mustofa Usman Nusyirwan Nusyirwan Oktavia, Putri Meyla Putri, Ayu Aulia Rahmadani, Tiara Sekar Rizky, Vega Bintang Saidi, Subian Salfadilah, Fatonah Siska Diah Ayu Larasati Siti Laelatul Chasanah, Siti Laelatul Sofalina Nodra Brilliantya Sutrisno, Agus Syach Alam, M. At-thariq Wibowo, Yusuf Rendi Widarti, Widiarti Wiranto, Ahmad Rizki WULANDARI Zakaria, La