<![CDATA[In general, the process of developing the beef agroindustry requires a planning strategy to consider the availability of resources and alternative processed products. The research aims to compare the accuracy of several forecasting methods for beef availability and determine the priority of beef processed products using Bayesian analysis. Annual population data on beef availability for the period 2015-2025 were analyze using a three year moving average (MA3), single exponential smoothing (SES) and linear trend regression. Forecast accuracy is determined based on the values of MAE, MSE and MAPE. Product prioritization is based on the assessment of 89 respondents regarding beef nuggets, sausages, jerky, and corned beef based on five criteria: market potential, added value, technological feasibility, environmental impact, and community acceptance. The weights of the criteria used are 0.30, 0.20, 0.20, 0.10, and 0.20 as per the planning weighting scenario. The research results show that SES produces the lowest MAE (1,841.71 tons) and MAPE (9.60%), while the linear trend model produces the lowest RMSE (2,438.39 tons). Based on the lower MAE and MAPE values, SES is used to estimate the beef production in Lampung Province in 2026 at 18,398.54 tons as an indicator of raw material availability from the regional production side. Products that can be used as alternative processed foods based on Bayesian analysis are beef nuggets with a score of 4.0416 for beef nuggets, 3.9360 for sausages, 3.8551 for corned beef, and 3.7719 for jerky. Beef nuggets received the highest priority score, particularly due to high ratings in market potential, added value, and public acceptance. Both analyses are used as a complementary two-stage decision support framework, thus serving as a basis for considering the management of processed products.]]>
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