2022Logaritma Jurnal Ilmu-ilmu Pendidikan dan SainsOpen access

Simple Linear Regression Method to Predict Cooking Oil Prices in the Time of Covid-19

Lilis Harianti Hasibuan, Darvi Mailisa Putri, Miftahul Jannah

Open full text 3 citations

Abstract

The background of this research is the soaring price of cooking oil during the Covid-19 period which continues to increase in the city of Padang. The research method used is a case study of data on cooking oil prices in the city of Padang. The purpose of this study is to obtain predictions of cooking oil prices. Linear regression is used as a prediction method for cooking oil prices in the next X(t) period. The research method used is a case study using simple linear regression. In this study, the actual cooking oil price Y(t) is the effect variable and the time period is the causal variable. The linear regression equation obtained is Y'=25239+124.56X. Testing the accuracy of the prediction results using RMSE with a value of 0.1913. The prediction of cooking oil prices using the linear regression method can be said to be in the very good category, it can be seen that the RMSE value is very small in the test and meets the standards.

Open-access reader

About this research paper

What this paper is about

The background of this research is the soaring price of cooking oil during the Covid-19 period which continues to increase in the city of Padang. The research method used is a case study of data on cooking oil prices in the city of Padang. The purpose of this study is to obtain predictions of cooking oil prices. Linear regression is used as a prediction method for cooking oil prices in the next X(t) period. The research method used is a case study using simple linear regression. In this study, the actual cooking oil price Y(t) is the effect variable and the time period is the causal variable. The linear regression equation obtained is Y'=25239+124.56X. Testing the accuracy of the prediction results using RMSE with a value of 0.1913. The prediction of cooking oil prices using the linear regression method can be said to be in the very good category, it can be seen that the RMSE value is very small in the test and meets the standards.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The background of this research is the soaring price of cooking oil during the Covid-19 period which continues to increase in the city of Padang. The research method used is a case study of data on cooking oil prices in the city of Padang. The purpose of this study is to obtain predictions of cooking oil prices. Linear regression is used as a prediction method for cooking oil prices in the next X(t) period. The research method used is a case study using simple linear regression. In this study, the actual cooking oil price Y(t) is the effect variable and the time period is the causal variable. The linear regression equation obtained is Y'=25239+124.56X. Testing the accuracy of the prediction results using RMSE with a value of 0.1913. The prediction of cooking oil prices using the linear regression method can be said to be in the very good category, it can be seen that the RMSE value is very small in the test and meets the standards.

Key concepts: Linear regression, Simple linear regression, Regression analysis, Statistics, Econometrics, Value (mathematics), Regression, Cooking oil

Related papers

Back to paper searchBrowse research topicsOriginal source
Simple Linear Regression Method to Predict Cooking Oil Prices in the Time of Covid-19 — Research Paper | ScholarLens