Prediksi Permintaan Reservasi Kamar Hotel Menggunakan Metode Fuzzy Time Series - Saputra, Habibi Yusup; Aziza, Istin Fitriani; Soraya, Siti (CORISINDO 2025, 2025)
Hotel reservation demand forecasting is a crucial component in hotel management for operational optimization and profitability. Time series reservation data is often volatile and uncertain, thus requiring an adaptive forecasting model. This study objective is to implements the Fuzzy Time Series (FTS) method to predict the number of weekly room reservations at a hotel in Gili Trawangan. Historical reservation data for 54 weeks from June 2024 to June 2025 is processed through three main stages: determining the universe of discourse, fuzzifying the data into seven fuzzy sets, and extracting knowledge to form Fuzzy Logical Relationship Groups (FLRG). The forecasting results are evaluated using actual data and show good model performance in capturing demand fluctuation patterns. The model accuracy measured by the Mean Absolute Percentage Error (MAPE) produces a value of 11.69%, indicating that FTS is an effective and promising method for forecasting hotel room demand with dynamic data characteristics.