FUZZY LOGIC FOR OPTIMIZING ROOM SALES: SUGENO METHOD AND MAPE EVALUATION

Abstract

The Indonesian hospitality industry has grown rapidly over the past decades and is one of the most important sectors of the national economy. The focus is on determining the number of rooms sold using the Sugeno method's fuzzy logic. This study optimizes room sales by developing a fuzzy logic-based system that can effectively determine the number of rooms sold considering availability, best available rates, and revenue target. The Sugeno method is a type of fuzzy inference system that determines the relationship between input variables (room availability, best available rate, revenue target) and output variables (number of rooms sold). Modeled by using linguistic variables and fuzzy rules, the Sugeno method can provide a quantitative output based on specified input conditions. To evaluate the accuracy of the proposed fuzzy logic model, the mean absolute percentage error (MAPE) is used as a performance measure. Target data 175,000,000 to 245,000,000, BAR standard room 225,000 to 335,000, BAR superior room 285,000 to 425,000, available standard room 68 rooms/day, superior room 10 rooms/day, model accuracy measurement result is 1,80% very accurate interpreted. As such, the proposed system is useful for decision-making related to optimizing room sales in the hospitality industry.