Fuzzy Inference with Probabilistic Rule Weighting to Assess Paragliding Viability Based on Weather Variables - Davianda Ersya Putri Della Adelia; Azwar Riza Habibi (UPT P2M State Polytechnic of Malang, 2026)
Paragliding is an extreme sport and tourism activity that is influenced by unpredictable and dynamic weather conditions, requiring a method capable of systematically handling this uncertainty to assist tourists and novice pilots in making flight scheduling decisions. This study focuses on experimenting with the application of probabilistic fuzzy logic in assessing the feasibility of paragliding in the Mount Banyak area, Batu City. The developed system combines the concept of fuzzification to model the uncertainty of meteorological parameters with a probabilistic approach at the inference stage to represent the level of confidence in each rule used. The experiment was conducted using actual weather data obtained through an Application Programming Interface (API) from open meteorological sources. The output of this method is a recommendation in three categories: “safe”, “caution,” and “dangerous.” Testing was conducted by comparing the system's predictions with actual data in the field and showed a Mean Absolute Percentage Error (MAPE) value of 9,77%. As a result, this system is capable of providing quick and accurate assessments that aid decision-making to improve the safety and operational efficiency of paragliding in the region. This approach shows broad application potential in other weather-based tourism fields, as well as supporting the development of environmentally friendly and sustainable technologies.