Rancangan Sistem Monitoring Suhu, Kelembaban, Kecepatan Angin Untuk Memprediksi Keamanan Jalur Pendakian

Abstract

Mountain climbing activities pose risks to climbers because they can cause serious injuries and often result in death, so weather information in mountainous areas is essential for predicting safety on climbing routes. In this study, the Internet of Things with a Decision Tree algorithm was used to build a real-time weather monitoring system and obtain data on weather conditions on mountain climbing routes. This study aims to measure the accuracy of the Decision Tree algorithm in classifying safety conditions and to develop a web-based application capable of displaying real-time data on temperature, humidity, and wind speed. The results of this study indicate that the use of the Decision Tree algorithm for classifying safety on hiking trails demonstrates very high accuracy, with an accuracy rate of 99.27%. Thus, the classification model built is highly effective in distinguishing between safe and hazardous conditions based on these three weather parameters. The very high accuracy indicates that the Decision Tree model used is highly suitable for application in prediction or monitoring systems, as developed in this study.