Peramalan Tingkat Penghunian Kamar (TPK) pada Hotel Berbintang di Banyuwangi dengan Metode Naive dan Decomposition

Randhi Nanang Darmawan (Politeknik Negeri Banyuwangi, Indonesia)
Jemi Cahya Adi Wijaya (Politeknik Negeri Banyuwangi, Indonesia)
Adetiya Prananda Putra (Politeknik Negeri Banyuwangi, Indonesia)

G-Tech : Jurnal Teknologi Terapan
Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024

One crucial element of managerial planning within the tourism and hospitality sector is utilizing historical data to forecast trends. This study aims to predict time series data for the Room Occupancy Rate (ROR) in Banyuwangi's starred hotels, considering that the increase in the number of tourist visits in Banyuwangi after the Covid-19 pandemic is quite high, and this is directly proportional to the Room Occupancy Rate. The study utilized Naive and Decomposition (Additive and Multiplicative) methods with time series data collected on a monthly basis from 2021 to 2023. The study compared the performance of the two methods. The study's results demonstrate that the Decomposition Method outperforms the Naïve method, with an average ROR value of 60.13% for the Additive model, along with MAD = 4.91%, RMSE = 6.708%, and MAPE = 10.85%. Similarly, the ROR value for the Multiplicative model yields a percentage of 61.26%, accompanied by MAD = 4.93%, RMSE = 6.73%, and MAPE = 10.78%. Therefore, based on this model, the ROR forecast value for the star hotels in Banyuwangi can be obtained for several month periods in the following year.