Mohammad Fikri - Academia.edu (original) (raw)
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Papers by Mohammad Fikri
Agroland: Jurnal Ilmu-ilmu Pertanian, Dec 30, 2019
This study aimed to determine the effect of farming intensification on the production of lowland ... more This study aimed to determine the effect of farming intensification on the production of lowland rice in West Tolai Village, Torue District of Parigi Moutong Regency. The variables used in the model production of the lowland rice farming were land area (X1), seed (X2), labor (X3), urea fertilizer (X4), and NPK fertilizer (X5). Data was analyzed using the Cobb-Douglas production function to determine the effect of the farming intensification to the production of the lowland rice. The results showed that such variables as land area (X1), seed (X2), labor (X3), and NPK fertilizer (X5) simultaneously had a significant effect on the rice production whereas the urea fertilizer (X4) is the only variable that did not significantly affect the rice production. The value of R 2 = 0.997 suggesting that the variables used in the model affect the production by 99.7% whereas, 0.30% is influenced by other factors not included in the model.
Agroland: Jurnal Ilmu-ilmu Pertanian, Dec 30, 2019
This study aimed to determine the effect of farming intensification on the production of lowland ... more This study aimed to determine the effect of farming intensification on the production of lowland rice in West Tolai Village, Torue District of Parigi Moutong Regency. The variables used in the model production of the lowland rice farming were land area (X1), seed (X2), labor (X3), urea fertilizer (X4), and NPK fertilizer (X5). Data was analyzed using the Cobb-Douglas production function to determine the effect of the farming intensification to the production of the lowland rice. The results showed that such variables as land area (X1), seed (X2), labor (X3), and NPK fertilizer (X5) simultaneously had a significant effect on the rice production whereas the urea fertilizer (X4) is the only variable that did not significantly affect the rice production. The value of R 2 = 0.997 suggesting that the variables used in the model affect the production by 99.7% whereas, 0.30% is influenced by other factors not included in the model.