Implementasi Association Rule pada Sistem Rekomendasi Peningkatan Hasil Pertanian Menggunakan Metode Apriori

The rapid development of technology increases the need for effective and efficient information. Information that is not managed properly loses value, especially when large amounts of data are available, making conventional methods no longer adequate to analyze the potential of the data. Therefore, a system capable of analyzing, summarizing, and extracting data into useful information is required. The Department of Agriculture and Food Security, as an agency that handles food security, agriculture, animal husbandry, animal health, and fisheries, is responsible for supporting the increase in agricultural yields to meet the food needs of the population and encourage economic growth. To achieve this goal, the agency needs to utilize technology to process agricultural data quickly and accurately. The system built using the apriori method can analyze data efficiently and provide recommendations for increasing agricultural yields. Based on the test results, a support value of 9% and a confidence of 68% were obtained, with the rule If the crop is Cassava, then the production yield is 6000-8000 tons.