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This study aims to analyze and project consumer prices of cabbage commodities at four levels: Ngawi Regency, Pacitan Regency, East Java Province, and nationally, using the additive Holt–Winters forecasting model. Monthly price data for the period January 2020–December 2024 were used to capture the dynamics of levels, trends, and seasonal patterns that affect price fluctuations. Model performance was evaluated using the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) indicators. The results showed differences in model accuracy between regions. East Java Province produced the best performance with the lowest MAE and RMSE values, indicating a more stable price pattern that was easier for the model to capture. In contrast, Ngawi Regency showed the highest volatility, resulting in greater forecasting errors. Pacitan Regency displayed a relatively consistent seasonal pattern with moderate accuracy, while national data showed smoother fluctuations due to the aggregation effect. Overall, the additive Holt–Winters model is effective for short-term projections in regions with low to moderate variability, but is less optimal in regions with highly volatile price dynamics.

Employees are Human Resources who are very important to achieve the company's vision and mission. Employees have a significant impact on the company's growth and ability to compete in the market. One way to create quality human resources, we need a system to determine exemplary employees. One way to determine employees by using a decision support system. Decision support systems are made to determine exemplary employees in a company based on predetermined weights. The method used in this system is Simple Additive Weighting because it has the advantage of being able to determine the weight value of each attribute. The results obtained from calculations using this system are the names of exemplary employees who have been sorted according to their ranking from the top to the bottom and this system can be used by companies to make it easier to give rewards or appreciation in determining exemplary employees.