Epsilon: Jurnal Matematika Murni dan Terapan
Vol. 16(2), 2022

INFERENSI MODEL REGRESI LINEAR UNTUK EKSPOR DAN IMPOR PROVINSI KALIMANTAN SELATAN TAHUN 2020

Nur Salam (lambung mangkurat university)
Fuad Muhajirin Farid (Lambung Mangkurat University)
Zainal Zainal (Student of Lambung Mangkurat University)



Article Info

Publish Date
01 Dec 2022

Abstract

Regression analysis is a statistical technique used to explain the relationship between an independent variable (independent) as a predictor variable (X) and the dependent variable as a response variable (Y) which can be expressed as a form of mathematical model. In linear regression analysis there are two models, namely a simple linear regression model where the independent variable is only one and a multiple linear regression model where the independent variable is more than one. This study aims to infer the parameters of the linear regression model both estimation and hypothesis testing and to apply the inference results to the export and import case of South Kalimantan province in 2020. This research method uses a literature study by collecting all materials and data, be it books, journals, web.site or other references that support and are relevant to the material to be discussed and researched. From the results of research on exports and imports of South Kalimantan province in 2022, inference results are obtained in the form of explicit forms for each parameter for point and interval estimates from linear regression models. Furthermore, an inference is obtained about hypothesis testing for each parameter, the results of which show that both significant parameters are included in the linear regression model

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Journal Info

Abbrev

epsilon

Publisher

Subject

Decision Sciences, Operations Research & Management Transportation

Description

Jurnal Matematika Murni dan Terapan Epsilon is a mathematics journal which is devoted to research articles from all fields of pure and applied mathematics including 1. Mathematical Analysis 2. Applied Mathematics 3. Algebra 4. Statistics 5. Computational ...