Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Arif Semar, Fitria Virgantari, Hagni Wijayanti

Judul : PERBANDINGAN ESTIMASI S (SCALE) DAN ESTIMASI MM (METHOD OF MOMENT) PADA MODEL REGRESI ROBUST DENGAN DATA PENCILAN

Abstrak :
Regression model is a model used to describe the relationship between dependent and independent variables. One method that is often used to estimate the parameters of a regression model is the OLS (Ordinary Least Square) method. In the regression model it is possible that there are outliers that cause some of the regression assumptions are violated so that the predicted value becomes inaccurate. There is method that can handle outlier can be used. One of them is the robust regression method using estimations S (Scale) and MM (Method of Moment). Those methods has a high breakpointthat is maximum amount of outliers data that can be tolerated by a model. This study aims to apply and compare OLS estimates, S estimates and MM estimates that contain outliers data. The data used are secondary data in the form of the ability to read a group of children aged 4 to 7 years, age, memory scores and IQ. The results showed the S estimation robust regression method is the best method compared to OLS estimation and MM estimation because it has the highest R2 value of 94.29%. Based on the S estimation method obtained by the model Y = -1,107 + 0,484X_1 + 0.052X_2 + 0.045X_3 where Y is the reading score of children aged 4 to 7 years, X1 is age, X2 is the memory score and X3 is IQ.

Tahun : 2020 Media Publikasi : Jurnal Nasional Blm Akreditasi

Kategori : Jurnal No/Vol/Tahun : 1 / 2 / 2020

ISSN/ISBN : 2655-3724

PTN/S : Universitas Pakuan Program Studi : MATEMATIKA

Bibliography :
Indra S, Vionanda D, Sriningsih R. 2013. Pendeteksian Data Pencilan dan Pengamatan Berpengaruh pada Beberapa Kasus Data Menggunakan Metode Diagnostik. Journal of Mathematics. Vol. 2, No. 1, 67-74. Universitas Negeri Padang.

Kurniawati, LD. 2011. Kekekaran Regresi Linier Ganda dengan Estimasi MM (Method of Moment) dalam Mengatasi Pencilan. Skripsi. Yogyakarta: Universitas Negeri Yogyakarta
Pratitis WD dan Listyani E. 2016. Perbandingan Metode Estimasi-M , Estimasi-S , Dan Estimasi-MM Pada Model Regresi Robust Untuk Memprediksi Produksi Kedelai Di Indonesia. Jurnal Pendidikan Matematika dan Saint. Vol. 5, No. 5. Universitas Negeri Yogyakarta
Riadi E. 2014. Metode Statistika Parametrik & Nonparametrik. Pustaka Mandiri. Tangerang.
Romdi, Wahyuningsih S, dan Yuniarti D. 2015. Regresi Robust Linear Sederhana dengan Menggunakan Estimasi MM (Method of Memont). Jurnal Eksponensial. Vol.6. No. 2. Universitas Mulawarman. Samarinda.
Sahari R. 2012. Model Produksi Jagung di Indonesia Menggunakan Regresi Robust Estimasi S. Skripsi. Universitas Sebelas Maret.

URL : http://openjournal.unpam.ac.id/index.php/sm/article/view/4207

Document

back

@official_unpak	@unpak
@unpak	UNPAK TV

Welcome Repository Universitas Pakuan

Student's Achievments

Unggul, Mandiri & Berkarakter

Detail Karya Ilmiah Dosen

Arif Semar, Fitria Virgantari, Hagni Wijayanti

Judul	:	PERBANDINGAN ESTIMASI S (SCALE) DAN ESTIMASI MM (METHOD OF MOMENT) PADA MODEL REGRESI ROBUST DENGAN DATA PENCILAN
Abstrak	:	Regression model is a model used to describe the relationship between dependent and independent variables. One method that is often used to estimate the parameters of a regression model is the OLS (Ordinary Least Square) method. In the regression model it is possible that there are outliers that cause some of the regression assumptions are violated so that the predicted value becomes inaccurate. There is method that can handle outlier can be used. One of them is the robust regression method using estimations S (Scale) and MM (Method of Moment). Those methods has a high breakpointthat is maximum amount of outliers data that can be tolerated by a model. This study aims to apply and compare OLS estimates, S estimates and MM estimates that contain outliers data. The data used are secondary data in the form of the ability to read a group of children aged 4 to 7 years, age, memory scores and IQ. The results showed the S estimation robust regression method is the best method compared to OLS estimation and MM estimation because it has the highest R2 value of 94.29%. Based on the S estimation method obtained by the model Y = -1,107 + 0,484X_1 + 0.052X_2 + 0.045X_3 where Y is the reading score of children aged 4 to 7 years, X1 is age, X2 is the memory score and X3 is IQ.
Tahun	:	2020	Media Publikasi	:	Jurnal Nasional Blm Akreditasi
Kategori	:	Jurnal	No/Vol/Tahun	:	1 / 2 / 2020
ISSN/ISBN	:	2655-3724
PTN/S	:	Universitas Pakuan	Program Studi	:	MATEMATIKA
Bibliography	:	Indra S, Vionanda D, Sriningsih R. 2013. Pendeteksian Data Pencilan dan Pengamatan Berpengaruh pada Beberapa Kasus Data Menggunakan Metode Diagnostik. Journal of Mathematics. Vol. 2, No. 1, 67-74. Universitas Negeri Padang. Kurniawati, LD. 2011. Kekekaran Regresi Linier Ganda dengan Estimasi MM (Method of Moment) dalam Mengatasi Pencilan. Skripsi. Yogyakarta: Universitas Negeri Yogyakarta Pratitis WD dan Listyani E. 2016. Perbandingan Metode Estimasi-M , Estimasi-S , Dan Estimasi-MM Pada Model Regresi Robust Untuk Memprediksi Produksi Kedelai Di Indonesia. Jurnal Pendidikan Matematika dan Saint. Vol. 5, No. 5. Universitas Negeri Yogyakarta Riadi E. 2014. Metode Statistika Parametrik & Nonparametrik. Pustaka Mandiri. Tangerang. Romdi, Wahyuningsih S, dan Yuniarti D. 2015. Regresi Robust Linear Sederhana dengan Menggunakan Estimasi MM (Method of Memont). Jurnal Eksponensial. Vol.6. No. 2. Universitas Mulawarman. Samarinda. Sahari R. 2012. Model Produksi Jagung di Indonesia Menggunakan Regresi Robust Estimasi S. Skripsi. Universitas Sebelas Maret.
URL	:	http://openjournal.unpam.ac.id/index.php/sm/article/view/4207