Artificial Intelligence-Based Irrigation Monitoring Information System For Enhancing Irrigation Rehabilitation Work Supervision

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Authors: Nurlaelah Nurlaelah, Satyanto Krido Saptomo, M. Yanuar J. Purwanto
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Abstract

The rehabilitation of irrigation networks plays a critical role in enhancing agricultural productivity and supporting national food self-sufficiency targets as mandated by Presidential Instruction No. 2 of 2025. Traditional monitoring practices still rely on manual reporting, inconsistent documentation, and non–real-time inspections, leading to data inaccuracies and limited transparency. These challenges highlight the need for a more reliable, timely, and objective monitoring system. SIMORI (Irrigation Monitoring Information System) is introduced as an AI-powered digital solution capable of providing real-time data, detecting anomalies, and generating accountable automated reports. This paper explores the relevance and urgency of SIMORI as a strategic instrument to enhance transparency, accountability, and monitoring quality in irrigation rehabilitation projects, thereby accelerating national food security objectives.

Fields of Study & Subjects

Smart Agriculture and AI Engineering and Agricultural Innovations Environmental Monitoring and Data Management

Publication details

Journal / source
Jurnal Indonesia Sosial Sains
Volume
7
Issue
1
Pages
93–100
Publication date
14 January 2026