Model Estimasi Produksi Padi Menggunakan Analisis Regresi Data Panel Di Provinsi Sumatera Utara Berdasarkan Data Tahun 2015-2019

Authors

  • Fuji Hidayah Universitas Sumatera Utara
  • Mardiningsih Mardiningsih universitas sumatera utara

DOI:

https://doi.org/10.55606/jurrimipa.v2i1.722

Keywords:

Rice Production, Analysis of Panel Data Regression, Estimation, Common Effect Model, Fixed Effect Model, Random Effect Model

Abstract

Analysis of panel data regression is a regression method to determine the relationship between the independent variable and the dependent variable using combined data, namely between cross-section data and time-series data.Analysis of panel data regression can apply to the processing of rice production estimates for an area including the province of North Sumatera. North Sumatera is one of the provinces in Indonesia, at the very of the population focuses on the agricultural sector as the main livelihood in rice being the primary production. Based on data on the development of rice production at the Agriculture Office of North Sumatra Province, the level of rice production in 2019 for North Sumatra Province reached 4,693,563 Ton/Year.Throught Panel Data Regression Analysis with the three approach methods is Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM) , the best approach method is obtained, namely the Fixed Effect Model (FEM) with the best estimation model is . The coefficient of determination  of 0.950890, which means that the independent variable affects the dependent variable by 95.08% on rice production.Based on the estimation model, the development of rice production in the next 3 years, namely 2020, 2021 and 2022, has changes of around 39.88% (decrease), 10.68% (increase), 9.89% (increase).

References

Drafer, N.R. Smith, H. 1972. Analisis Regresi Terapan Edisi Kedua. Jakarta : PT Gramedia Pustaka Umum.

Gunawan, Imam. 2017. Pengantar Statistika Inferensial. Jakarta : Rajawali Pers.

Meutuah, S. M., Yasin, H., dan Maruddani, S.A.I. 2017. ”PemodelanFixed Effect Geographically Weighted Panel Regression untukIndeks Pembangunan Manusia di Jawa Tengah”.”Jurnal Gaussian”. Vol 6,no 2. Hal 241-250.

Refnaldo, Maiyastri, dan Asdi.2018. “Analisis Ketahanan Pangan Provinsi Sumatera Barat Dengan Metode Regresi Data Panel”. “JurnalMatematika UNAND”. vol 7, no. 2. Hal 39-49.

Sofyan, Y. Lien, A.R dan Kurniawan, H.2004.Regresi dan Korelasi Dalam Genggaman Anda. Jakarta : Salemba Empat.

Spiegel, M.R. Stephens, L.J. 2004.Statistika Edisi Keiga. Jakarta : Erlangga.

Sudiartanto. Suwarno, N. dan Taofik, A.2017. ”Ridge-MM Sebagai Salah Satu Metode Regresi Ridge Yang Robust Terhadap Data Pecilan”. ”Jurnal FMIPA UNPAD”. vol 10, no 1. Hal 37-51.

Suharyadi dan Purwanto, S.K.2003. Statistika Untuk Ekonomi dan Keuangan Modern. Jakarta : SalembaEmpat.

Supranto, J.2008. Statistika Teori dan Aplikasi Edisi Ketujuh. Jakarta : Erlangga.

Youssef, A.H., Abonazel, M.R., dan Ahmed, E.G.2020. “Estimating The Number Of Patent in The World Using Count Panel Data Models”.”Asian Journal of Probability And Statistics”. Vol 6 no 4. Hal 24-33.

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Published

2023-01-15

How to Cite

Fuji Hidayah, & Mardiningsih Mardiningsih. (2023). Model Estimasi Produksi Padi Menggunakan Analisis Regresi Data Panel Di Provinsi Sumatera Utara Berdasarkan Data Tahun 2015-2019. JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM, 2(1), 61–75. https://doi.org/10.55606/jurrimipa.v2i1.722