Regression Model of Land Area and Amount of Production to the Selling Price of Corn

  • Astriyani Oktafian Universitas Muhammadiyah Mataram, Indonesia
  • Vera Mandailina Universitas Muhammadiyah Mataram, Indonesia
  • Mahsup Mahsup Universitas Muhammadiyah Mataram, Indonesia
  • Wasim Raza University of Sargodha, Pakistan
  • Kirti Verma Lakshmi Narain College of Technology, India
  • Syaharuddin Syaharuddin Universitas Muhammadiyah Mataram, Indonesia
Keywords: Amount of Production, Double Linear Regression, Land Area, Modelling, The Selling Price of Corn

Abstract

Currently, land area, production and maize prices in West Nusa Tenggara province are sometimes unstable. One of the factors affecting the instability of maize prices is the shift in planting patterns at the farm level. The purpose of this study is to determine the effect of land area and total production on the selling price of maize. The method used is quantitative with data analysis techniques using multiple linear regression. The source of data is from the Central Bureau of Statistics, Department of Agriculture and Plantation of NTB. The regression equation found is Y = 3109.911 + 0.007X1 - 0.001X2. This result shows that the X1 variable of 0.007 means that every time there is an increase in the land area variable by 1%, the selling price increases by 7%. While the X2 variable decreased by 1%. The hypothesis with the calculation of the partial t-test of land area is 1.249, which means that land area has no influence on the selling price of NTB corn in 2012-2021. In future research, it is necessary to conduct research on the development of corn planting land area, production, productivity per unit of land area nationally associated with the rate of population growth, corn demand, and the growth of corn imports nationally.

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Published
2023-05-17
How to Cite
[1]
A. Oktafian, V. Mandailina, M. Mahsup, W. Raza, K. Verma, and S. Syaharuddin, “Regression Model of Land Area and Amount of Production to the Selling Price of Corn”, Jurnal Varian, vol. 6, no. 2, pp. 149 - 156, May 2023.
Section
Articles