Recently, the public has been confronted with scarce and expensive rice in the market. Many parties state that this price hike is partly due to the impacts of climate change, which has delayed planting schedules in the previous year (2023). The delayed harvest schedule is said to have reduced rice supplies, leading to high rice prices in the market.
According to agricultural meteorology, environmental science, and climate change observer from UGM, Dr. Bayu Dwi Apri Nugroho, the public should not only blame the delayed planting schedules due to climate change as the sole contributing factor. Instead, many parties should make plans to anticipate the uncontrolled rise in rice prices well in advance.
“One thing that can be done is to strengthen agricultural data. The utilization of information in agricultural production systems should be done through research approaches based on information and communication technology (ICT),” he explained at UGM on Wednesday (Mar. 20).
He mentioned that this technology allows for a more detailed recording of upstream and downstream processes, encompassing the environment and crops.
Data stored in databases will naturally grow larger over time as the observation process in production progresses. Analyzing large amounts of data or big data analysis is expected to provide farmers with an understanding by extracting valuable information that may enhance productivity.
“So far, big data analysis methods have been widely used to support industrial activities, but further exploration is still needed for agriculture,” he said.
For Dr. Nugroho, the village-level agricultural data development model is crucial because it relates to productivity improvement, determination of planted commodities, soil quality, pest and disease management, and much more.Â
This agricultural data can be captured or updated in real-time within a single data framework, enabling it to be processed and analyzed into accurate business decisions. Unfortunately, institutional issues, human resources, and information technology have been major challenges in agricultural data development.Â
The Ministry of Agriculture’s role in the village-level agricultural data development model is critical. It acts as a lead that is then delegated to regional levels, such as the respective Agricultural Offices, and then broken down further into smaller regions, such as districts and villages.
Data is inherently linked to ICT-related information, necessitating cooperation with Communication and Information Offices at the same level. The Ministry of Communication and Information Technology also plays a crucial role in agricultural data development by positioning itself under the coordination of the Ministry of Agriculture.Â
It coordinates with Agricultural Offices, Communication and Information Offices, and relevant regional governments regarding the use of information technology for agriculture.
“Data collection involves field personnel coordinated by Agricultural Offices through field facilitators. Depending on each region’s APBD, field personnel can be supplemented by recruiting field systems,” he explained.
Furthermore, Dr. Nugroho stated that village-level agricultural data development requires preparation and coordination between institutions and regional governments to run smoothly.Â
The existence of agricultural data at the village level will undoubtedly facilitate the government’s policies that meet the needs of farmers in the field.
He mentioned that technology mapping can be achieved by examining this single data. The Ministry of Communication must prevent overlapping with other ministries or agencies, such as Statistics Indonesia and the Ministry of Agriculture.
“The synchronization of data for analysis and prediction is one of the essential things that must be met in the agricultural sector. In this case, the effort to use integrated single data among relevant bodies is the right solution so that accurate data can be used as the basis for decisions and policies in the agricultural sector, such as rice import decisions, including as a step to anticipate the impacts of climate change such as El Nino and La Nina phenomena,” he concluded.
Author: Agung Nugroho
Image: Freepik.com