Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra - Rizki Akbar; Fitri, Fadhilah; Vionanda, Dodi; Mukhti, Tessy Octavia (Universitas Negeri Padang, 2024)
The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.