Utilization System Big Data -Based Pest Prediction in Plants Horticulture : Study Cases in Tropical Regions

Attack difficult pests​ predicted is challenge main in cultivation plant horticulture in tropical regions . Research This aim For evaluate utilization system prediction pest big data based designed For give warning early and recommendations more control​ accurate . Approach research used​ is qualitative with method studies case to three group farmer horticulture in tropical Indonesia. Data collected through interview in-depth , observation field , and documentation use A predictive digital system that integrates microclimate data , field sensors , and machine learning algorithms . Research results show that use system This lower intensity attack pest by 30–50% and increase efficiency use pesticides . Farmers with greater digital literacy tall show level adoption more systems​ good . Findings This give contribution important for development system agriculture adaptive precision​ to change climate tropical and can push taking decision data- based at the level field .

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Publication Details

Journal
Digital Agriculture and Innovation Journal
Published
2025-08-25
DOI
https://doi.org/10.59261/journaldaij.v1i2.9
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Utilization System Big Data -Based Pest Prediction in Plants Horticulture : Study Cases in Tropical Regions

Sri Wahyuni Lubis
Digital Agriculture and Innovation Journal
Smart Agriculture and AI
article

Utilization System Big Data -Based Pest Prediction in Plants Horticulture : Study Cases in Tropical Regions

Sri Wahyuni Lubis
article en

Abstract

Attack difficult pests​ predicted is challenge main in cultivation plant horticulture in tropical regions . Research This aim For evaluate utilization system prediction pest big data based designed For give warning early and recommendations more control​ accurate . Approach research used​ is qualitative with method studies case to three group farmer horticulture in tropical Indonesia. Data collected through interview in-depth , observation field , and documentation use A predictive digital system that integrates microclimate data , field sensors , and machine learning algorithms . Research results show that use system This lower intensity attack pest by 30–50% and increase efficiency use pesticides . Farmers with greater digital literacy tall show level adoption more systems​ good . Findings This give contribution important for development system agriculture adaptive precision​ to change climate tropical and can push taking decision data- based at the level field .

Digital Agriculture and Innovation JournalVol. 1(2)
Openalex Percentile: Top 78%
Smart Agriculture and AI
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