The influence of labor and land use management on rice farming production in Pohuwato District

Abstract

The purposes of this research are: 1) to analyze the labor and land use area in Pohuwato District; 2) to analyze the effect of labor and land area usage on increased rice production in Pohuwato; 3) to analyze the factors of soil processing technology that have influence on rice production in Pohuwato District. The research method is survey method. The data analysis is descriptive analysis and multiple linear regression analysis. The results showed that the labor use in family and land are has a significant effect on rice production in Pohuwato District of Gorontalo. The other side that the technologies increase has no significant effect on rice production in Pohuwato District of Gorontalo. The results that showed insignificant effect because the technology has a good impact in increased production but not factual, so in the future it the need to evaluate in the technology adoption and the role of agricultural extension must be more optimal.

Comparing productivity of rice under system of rice intensification and conventional flooding: A switching regression approach

“…Therefore labor is an integral variable to determine the productivity of the technology. The findings are consistent with the findings of Canon et al (2018), Adesina and Zinnah (1993), Karki (2010) and Karubanga et al (2019).…”

Beta four parameter GLMM approach to evaluate paddy productivity

“…Assessment wise, we also hope to also convince that researchers should consider the random effects approach in modeling paddy productivity. Area characteristics can be modelled, allowing better understanding on the effect of different areas towards different average paddy productivity outcomes by using random coefficients [7]. Better policy-relevant inferences can also be obtained from random effects models [7].…”

“…Area characteristics can be modelled, allowing better understanding on the effect of different areas towards different average paddy productivity outcomes by using random coefficients [7]. Better policy-relevant inferences can also be obtained from random effects models [7].…”

Pengaruh Luas Lahan dan Jumlah Tenaga Kerja terhadap Produksi Padi di 10 Kabupaten Jawa Timur Tahun 2014-2018

“…Tabel 2 menunjukkan rata-rata jumlah produksi padi di 10 daerah Lumbung Padi di Jawa Timur, tahun 2014-2018. Rata-rata jumlah produksi terbanyak di tiga daerah yaitu Kabupaten Jember, Kabupaten Banyuwangi, Kabupaten Pasuruan Penelitian sebelumnya menemukan adanya dampak luas lahan terhadap produksi padi, seperti penelitian Usman dan Juliyani (2018), Andrias, dkk (2017), Gunawan (2018), Hartati, Budhi, dan Yuliarmi (2017), Canon, Halid, dan Daud (2018, Pudaka, Rusdarti, & Prasetyo (2018), yang menemukan dampak luas lahan serta tenaga kerja terhadap produksi padi secara parsial positif dan signifikan. Pada beberapa penelitian tersebut hanya meneliti sebatas Kabupaten tertentu, sedangkan dalam penelitian ini akan meneliti pada Kabupaten/Kota dalam Provinsi Jawa Timur.…”

“…e-ISSN2745-6366 Pada beberapa penelitian sebelumnya juga menemukan adanya pengaruh tenaga kerja terhadap produksi padi seperti penelitian Usman dan Juliyani (2018), Astari dan Setiawina (2016), Canon, Halid, dan Daud (2018) yang menemukan adanya dampak signifikan secara positif tenaga kerja terhadap peningkatan produksi padi. Namun hasil yang berbeda ditemukan dalam penelitian yang dilakukan oleh Gunawan (2018) yang mana hasilnya membuktikan bahwa tenaga kerja berdampak negative dan tidak signifikan terhadap produksi padi.…”