Research Article
Development of a Sustainable Replanting Simulation System
@INPROCEEDINGS{10.4108/eai.24-10-2023.2343486, author={Mhd Dominique Mendoza and Fevi Rahmawati Suwanto and Ishaq Matondang}, title={Development of a Sustainable Replanting Simulation System}, proceedings={Proceedings of the 5th International Conference on Innovation in Education, Science, and Culture, ICIESC 2023, 24 October 2023, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2024}, month={1}, keywords={machine learning management information system replanting simulation}, doi={10.4108/eai.24-10-2023.2343486} }- Mhd Dominique Mendoza
Fevi Rahmawati Suwanto
Ishaq Matondang
Year: 2024
Development of a Sustainable Replanting Simulation System
ICIESC
EAI
DOI: 10.4108/eai.24-10-2023.2343486
Abstract
Replanting is a crucial agricultural procedure that entails the substitution of harvested crops with fresh onesThe process entails the acquisition of diverse data sets essential for comprehending the system under consideration for modeling purposes, alongside their integration into a cohesive database. In the realm of agricultural simulation system development, the necessary data encompasses several elements such as soil conditions, historical weather data, crop production estimates, market pricing, and additional economic aspects. A simulation model was designed to include machine learning methods for the purpose of predicting agricultural yields in varying environmental circumstances. The implementation of a sustainable replanting simulation system signifies a notable advancement in the promotion of agricultural methods that prioritize sustainability. This system offers decision-makers a robust tool for the planning and management of replanting efforts by incorporating data analytics and simulation methodologies