Artificial Intelligence Application For Precision Agriculture In Indonesia That Promises

YOGYAKARTA - In the midst of several companies that are increasingly pressing the agricultural sector, such as land constraints, climate change, and increasing food needs, innovative solutions are increasingly needed.

One of the increasingly eyed solutions is the application of artificial intelligence (AI) in precision agricultural practices in Indonesia. This article will review artificial intelligence applications for precision agriculture in Indonesia.

Reporting from West Sciences, precision agriculture is an approach that utilizes data and technology to manage agriculture more specifically and efficiently. Examples regulate plant monitoring, fertilization, irrigation, and others based on real conditions of land and plants.

In this case, AI holds an important function in the analysis of large data (big data), predictions of yields, satellite or drone image processing, or early detection of pests/diseases. A review of the literature explains that technologies such as drones, IoT, robots, and AI are an important part of precision agricultural innovation with the aim of increasing productivity and sustainability.

In Indonesia, the development of 'smart farming 4.0' with an AI basis has been established as one of the strategies to achieve advanced, independent, and modern agriculture.

Some of the main benefits that can be obtained by farmers and agribusiness actors by implementing AI in precision agriculture include:

Early detection of pests/diseases and plant monitoring: AI can process images from drones or cameras to recognize areas of plants that are stressed or exposed to pests, so interventions can be carried out more quickly. The article "Optimizing Indonesian Agriculture through Artificial Intelligence" refers to the detection of pests/diseases as one of AI's main contributions.

Efficiency in resource utilization: With AI and sensors, fertilization, irrigation system, or pest control, it can be done with real-time data and land specific conditions so that waste of water, fertilizer, or pesticides can be reduced.

A study on dry land (NTT) concluded that AI integration and satellite imagery increased the efficiency of water distribution by 30% and the accuracy of yield predictions by more than 85%.

Improved yields and plant quality: in Indonesia, companies that use AI-based analytics for oil palm plantations explain that they get recommendations for fertilization that increase efficiency by about 20%.

Data-based decision-making: With AI-based applications, farmers can get recommendations for when to plant, when to cultivate, when to harvest, and everything based on land data, weather, and soil fertility levels. One application used in Indonesia is BIBIT.AI which provides recommendations for plants and real-time weather.

Several studies and projects in Indonesia prove how the application of AI in precision agriculture applies:

That's a review of artificial intelligence applications for precision agriculture in Indonesia. Hopefully useful! Visit VOI.id to get other interesting information.