Strategi Meningkatkan Daya Saing Bawang Merah Melalui Prediksi Harga

Shallots contribute significantly to the formation of food commodity inflation caused by high price fluctuations. Precise price forecasting is vital for all agribusiness actors, from farmers, traders, and consumers to production and inventory management. This research aims to identify the forecasting prices for shallot producers and consumers and formulate strategies to increase the competitiveness of shallots. This research uses the SARIMA method to capture seasonal elements in the data. The data used is time series data on shallot prices at the consumer and producer levels from January-November 2021. Determining the best SARIMA model uses the auto-arima technique, which shows that the best SARIMA for shallot prices at the producer level is ARIMA (2,1,2)(2,0,0)[12]. In contrast, the price of shallots at the consumer level is ARIMA (5,1,1)(1,0,1)[12]. The prediction results show that the dynamics of shallot prices in the future will continue to follow seasonal patterns as in previous years, namely, high prices during the lean season and religious holidays and low prices during the harvest season. The government needs to strengthen its policy of stabilizing shallot prices at both consumer and producer levels. Availability of agricultural inputs, adoption of technology for post-harvest and marketing, value-added innovation, and infrastructure improvements are strategic efforts to strengthen the competitiveness of shallots.