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dc.contributor.authorAmutuhaire, Mujaidu
dc.contributor.authorKwizera, Nicholas
dc.contributor.authorNakasango, Shariffa
dc.contributor.authorWangota, Felix Daniel
dc.date.accessioned2022-04-22T07:45:06Z
dc.date.available2022-04-22T07:45:06Z
dc.date.issued2021-12
dc.identifier.citationAmutuhaire, M., Kwizera, N., Nakasango, S., & Wangota, F. D. (2021). The idealcrop system. (Unpublished undergraduate dissertation). Makerere University, Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/11824
dc.descriptionA project report submitted to the School of Computing and Informatics Technology for the study leading to a project in partial fulfillment of the requirements for the award of the Degree of Bachelor of Science in Software Engineering of Makerere University.en_US
dc.description.abstractThis report is for the implementation of the IdealCrop System, from its design to completion. It is a web-based machine learning application that provides a service to farmers or farm managers, enabling them to make informed decisions on crop selection and care, and crop variety options to choose from while considering climatic factors, NPK soil nutrients, and best crop yield on a Ugandan district level.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectMachine Learningen_US
dc.subjectFarmingen_US
dc.subjectCropen_US
dc.titleThe idealcrop systemen_US
dc.typeThesisen_US


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