ESTIMATION OF COCONUT HARVEST YIELDS IN NORTH MALUKU PROVINCE USING THE ADAMS-BASHFORTH-MOULTON METHOD

The present research applies the Verhulst growth model and the Adams-Bashforth-Moulton numerical method to estimate coconut harvest yields in North Maluku Province. Using coconut harvest data from 2019 to 2023 obtained from Badan Pusat Statistika(BPS), the model was initialized through the fourth-order Runge-Kutta method to generate four initial values. These values were then used in the ABM method to predict yields for the period 2024 to 2033. The simulation results show a slow growth in harvestyields from 2024 to 2026, with an average increase of approximately 0.003% per year, followed by a significant increase in 2027. After that, the harvest yields stabilize near the carrying capacity of approximately 432,600 tons. In contrast, a notable decrease of 1.923% in coconut harvest yields was observed between 2022 and 2023, highlighting fluctuations prior to stabilization and confirming the characteristic behavior of the Verhulst model in modeling population or production dynamics.The results of this study can serve as a foundation for more effective agricultural production planning, supply chain optimization, and the formulation of food security policies in North Maluku Province. By understanding the growth patterns of harvest yields, local governments and industry stakeholders can design more targeted distribution and investment strategies.

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Journal
Parameter.
Published
2025-03-30
DOI
https://doi.org/10.30598/parameterv4i1pp01-10
Primary Topic
Agricultural and Environmental Management
Type
article
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article

ESTIMATION OF COCONUT HARVEST YIELDS IN NORTH MALUKU PROVINCE USING THE ADAMS-BASHFORTH-MOULTON METHOD

Monalisa E. Rijoly, Abraham Z. Wattimena, Majesty Pattipeiohy
Parameter.
Agricultural and Environmental Management
article

ESTIMATION OF COCONUT HARVEST YIELDS IN NORTH MALUKU PROVINCE USING THE ADAMS-BASHFORTH-MOULTON METHOD

Monalisa E. Rijoly, Abraham Z. Wattimena, Majesty Pattipeiohy
article en

Abstract

The present research applies the Verhulst growth model and the Adams-Bashforth-Moulton numerical method to estimate coconut harvest yields in North Maluku Province. Using coconut harvest data from 2019 to 2023 obtained from Badan Pusat Statistika(BPS), the model was initialized through the fourth-order Runge-Kutta method to generate four initial values. These values were then used in the ABM method to predict yields for the period 2024 to 2033. The simulation results show a slow growth in harvestyields from 2024 to 2026, with an average increase of approximately 0.003% per year, followed by a significant increase in 2027. After that, the harvest yields stabilize near the carrying capacity of approximately 432,600 tons. In contrast, a notable decrease of 1.923% in coconut harvest yields was observed between 2022 and 2023, highlighting fluctuations prior to stabilization and confirming the characteristic behavior of the Verhulst model in modeling population or production dynamics.The results of this study can serve as a foundation for more effective agricultural production planning, supply chain optimization, and the formulation of food security policies in North Maluku Province. By understanding the growth patterns of harvest yields, local governments and industry stakeholders can design more targeted distribution and investment strategies.

Parameter.Vol. 4(1)
University of Pattimura (ID)
Openalex Percentile: Top 79%
Agricultural and Environmental Management
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