RAGAM: Journal of Statistics and Its Application
Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application

ANALISIS REGRESI ROBUST M ESTIMATOR UNTUK MENGETAHUI FAKTOR YANG MEMPENGARUHI LAMA STUDI MAHASISWA S1 STATISTIKA FMIPA UNIVERSITAS LAMBUNG MANGKURAT

Widawati Annisa Putri (Universitas Lambung Mangkurat)
Fuad Muhajirin Farid (Universitas Lambung Mangkurat)
Selvi Annisa (Universitas Lambung Mangkurat)



Article Info

Publish Date
02 Jul 2024

Abstract

Robust regression is a statistical technique commonly used to model relationships between variables by minimizing the impact of outlier data. The use of robust regression M Estimator works well when there are outliers in the data. In this study, robust regression M estimator analysis will be applied to student study period data. The aim of this research is to determine the significant factors influencing the study period of Statistics undergraduate students at the Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. The results of the research show that the residual data characteristics are not normal and there are outliers in the data. Using the Robust Regression M Estimator, the F test results show that F calculated 6.2492 > F table 2.173112, which means rejecting H0, indicating that the independent variables collectively have a significant effect on the dependent variable. From the t-test, it is known that the Guidance Process for students while working on their final project, the Employment Status of students, and the GPA of students significantly affect the Study Period of students. Keywords:   Robust Regression M Estimator, Study Period of Students, ULM

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Journal Info

Abbrev

ragam

Publisher

Subject

Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health

Description

RAGAM Journal publishes scientific articles in the field of statistics and its applications, including: * Biostatistics * Parametric and nonparametric statistics * Quality control * Econometrics and business * Industrial statistics * Time series analysis * Spatial statistics * Data mining * ...