Dec 2026· Jurnal Pertanian Presisi (Journal of Precision Agriculture)· 0 citations
Smart Agriculture and AI
Abstract
Cassava (Manihot esculenta) is an important crop in Indonesia, but its productivity is often reduced by pests and diseases. This study aimed to identify the types of pests and diseases affecting cassava and to analyze the severity of infection using digital technologies. Observations were conducted on 23 November 2025 at three locations in Sempaja Utara, Samarinda, East Kalimantan. Leaf samples were identified using Plantix and Agri AI applications, while disease severity was analyzed by measuring the leaf area using ImageJ software. Results showed that sample A was affected by brown leaf spot and anthracnose, sample B was attacked by spider mites and Septoria leaf spot, and sample C was affected by spider mites and Cassava Brown Streak Disease (CBSD). ImageJ analysis indicated that the highest disease severity was 2.01% in sample B, and the lowest was 0.33% in sample A. These findings demonstrate that digital applications and artificial intelligence–based tools can support fast and efficient identification of cassava pests and diseases, providing potential guidance for better crop health management.
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