Corn production using Runge-Kutta and Least Square method / Zaidatul Hafizah Zakaria and Aisyatul Husna Mohd Suhaimi

Zakaria, Zaidatul Hafizah and Mohd Suhaimi, Aisyatul Husna (2019) Corn production using Runge-Kutta and Least Square method / Zaidatul Hafizah Zakaria and Aisyatul Husna Mohd Suhaimi. Degree thesis, Universiti Teknologi MARA.


The monthly production of the corn in Malaysia within a year is inconsistent. The Agriculture Industry including the farmers are facing problem to estimate the production of corn. This will affect to the Industry and farmers especially to their income, food supply for Food Industry and also satisfy or reach the demand. Malaysia nowadays needs to import the corn from other country. The cost is higher than Malaysia producing own corn. Therefore, a solution is needed to overcome this problem. If the industry is able to increase the production, then it will help the farmer to increase their monthly income. Moreover, it will help to improve country’s finance. The Objective of this research is to predict the next production of corn using the Runge-Kutta method and Least Square Method. In order to gain the accuracy of the purposed method, result from the actual production is compared to the numerical solution. Therefore, researcher can choose the most appropriate method to predict corn production for the next upcoming years. The best method to predict the corn production is using Runge-Kutta Method.


Item Type: Thesis (Degree)
Email / ID Num.
Zakaria, Zaidatul Hafizah
Mohd Suhaimi, Aisyatul Husna
Email / ID Num.
Thesis advisor
Mohd Yusof, Zanariah
Subjects: Q Science > QA Mathematics > Analysis > Differential equations. Runge-Kutta formulas
Q Science > QA Mathematics > Analysis > Difference equations. Functional equations. Delay differential equations. Integral equations
Q Science > QC Physics > Mathematical physics > Finite element method
Divisions: Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons) Computational Mathematics
Keywords: Agriculture Industry ; Runge-Kutta Method ; Food Industry ; Least Square Method
Date: July 2019
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