During this industrialization era, agriculture is still the key to the economic development of developing countries, such as Indonesia. This chapter aims to see how relevant the current agricultural model is. The method used is the literature review. With the development of digitalization, agriculture in Indonesia, which still uses little technology, must be encouraged to be more technologically literate. In the future, the government must pursue agricultural digitalization to increase the level of farmer welfare so that agriculture can become a driving sector for industrialization and economic growth.
TopThe Scope Of Digitalization In Agricultural Sector
Agricultural digitalization is a change and development of methods in agriculture, starting from the early planting period, processing, marketing to post-harvest. The development of traditional agricultural systems towards digitalization in agriculture is a possible solution to overcome the problems farmers face, both internally and externally. Therefore, the Ministry of Agriculture launched the Agriculture 4.0 program, precision agriculture combined with digital information technology, namely cloud computing, mobile internet, and big data (Ministry of Agriculture, 2019).
Cloud computing is a technology that utilizes the internet as central processing of applications and data, where users who have access rights can participate in managing them. One cloud computing implementation is digitizing agricultural training, for example, the integration of training reporting information systems, one-stop access to agricultural activity, and digital administration governance (Caya, 2020). Technology and internet-based applications, which are easier for farmers, have been widely developed by the Agricultural Research and Development Agency (Balitbang). Thus, farmers can take part in online training organized by the ministry of agriculture and other institutions to absorb information that has been integrated into one page using cloud computing.
In the agricultural sector, big data lead a significant role, like storing various data, including mapping agricultural land. The land mapping was accompanied by data collection on commodities and agricultural products (Wibowo & Dairoh, 2018). Apart from being owned by the Central Bureau of Statistics, this big agricultural data has also been developed by local governments, such as the Brebes Regency, which has set a system through the System Development Life Cycle method. The developed SDLC can facilitate and accelerate the flow of agricultural information so that the government can carry out the policymaking quickly and precisely.
According to Abiwodo (2021), the implementation of agricultural digitization is defined as smart farming, precision farming, precision agriculture, and smart agriculture. Precision agriculture is defined as a way for farmers to determine the proper techniques and inputs, where farmers can process to harvest with precision according to the information they get through the help of digital devices. For example, farmers can calculate the correct spacing. Then the farmers can obtain the farmers the need for seeds and fertilizers, even the quantity of crop yields correctly. Precision farming must be supported by GIS, GPS, pest sensors, plant sensors, soil sensors, and aerial photography to measure variables on agricultural land (Manalu, 2013). Therefore, precision agriculture can encourage sustainable agriculture.
The information obtained in digitization and various tools and machines resulting from technological developments can also benefit farmers. For example, they use advanced machinery such as planting robots, granular fertilizer drones, autonomous tractors, and integrated harvesting machines with tillage. In addition, other modern tools and machines integrated into digital systems can increase efficiency in resource use.