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Kusumasari, Pamelina Alisha
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Implementasi Geographically Weighted Regression (GWR) pada Determinasi Faktor Produksi Beras di Indonesia Tahun 2021 Wicaksono, Ditto Satrio; Kusumasari, Pamelina Alisha; Fajar, Huda M.; Fajritia, Rahajeng; Puspita Anggraini, I Gusti Ayu; Budiasih, Budiasih
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1714

Abstract

Food security is one of the nation’s responsibility in ensuring the appropriate and affordable foods for its citizens, especially rice. However, the rising number of agricultural land function conversion together with inequality rice production in every provinces still challenge our government in achieving the national food security. Understanding this situation, this research is conducted to analyze the factors influencing rice production in each province in Indonesia in 2021. To achieve this purpose, descriptive analysis and inferential analysis are employed, utilizing the Geographically Weighted Regression due to the spatial factors involved in each province and the occurrence of spatial heterogeneity from the global model. GWR model shows a better performance compared to global model in modelling the rice production growth in Indonesia. The results shows that there are six regional groups based on significant variables. Furthermore, labor still be the main factor in increasing rice production across all provinces also the intensity of fertility must be considered in order to achieve food security in Indonesia.
Co-Authors Budiasih Budiasih Fajar, Huda M. Fajritia, Rahajeng Puspita Anggraini, I Gusti Ayu Wicaksono, Ditto Satrio