Room Occupancy Rate (ROR) is an important indicator of hotel performance and serves as a basis for operational planning and managerial decision-making. Fluctuations in ROR influenced by trend and seasonal patterns require hotels to use accurate forecasting methods to anticipate changes in demand. This study aims to analyze the characteristics of Room Occupancy Rate (ROR) data, generate ROR forecasts using the Holt-Winters Additive method, analyze the accuracy and feasibility of the forecasting model, and examine the implications of the forecasting results for managerial decision-making at Sadara Resort Tanjung Benoa, Bali. This study employs a quantitative approach using a time series method. The data consist of monthly ROR data from Sadara Resort for the period of January 2023 to June 2026, comprising 42 observations. The Holt-Winters Additive method was selected because the data demonstrate trend and seasonal patterns. Model accuracy and feasibility were evaluated using MAPE, MAE, RMSE, Stationary R-squared, R-squared, and the Ljung-Box Q test. The research results indicate that the Room Occupancy Rate (TPK) data exhibits fluctuation and seasonal patterns that recur annually. The Additive Holt-Winters model yielded a MAPE of 6.242%, an MAE of 4.806, and an RMSE of 7.073. The MAPE value was calculated based on model-building data from January 2023 to June 2026 and falls into the "highly accurate" category according to Lewis's (1982) criteria. The Ljung-Box Q test result showed a significance value of 0.487 (> 0.05); thus, the residuals do not exhibit significant autocorrelation, and the model is deemed suitable for generating future forecasts. Forecasting results for the period of July 2026 to December 2027 indicate that the highest projected TPK is 96.80% in August 2027, while the lowest is 64.70% in March 2027. Based on this evaluation, the Additive Holt-Winters model demonstrates an excellent fit with the model-building data and is suitable for estimating future TPK. Sadara Resort can utilize these forecasting results to formulate revenue management, operational, budgetary, and marketing strategies aligned with demand conditions for each period.
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Yastiari et al. (2026) studied this question.
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