Penerapan Data Mining Untuk Memprediksi Harga Udang Vaname Di Pasar Lokal Menggunakan Algoritma Decision Tree - Gunawan Gugun (Riset Sinergi Indonesia (RISINDO), 2025)
This research aims to predict the price of vaname shrimp in the local market of Padang City using the Decision Tree algorithm. The data used includes historical records of shrimp prices from 2024 to 2025, along with supporting variables such as production volume, feed prices, weather conditions, pond type, and market conditions. The research methodology includes data collection, preprocessing, algorithm implementation, model evaluation, and system development. The results show that the Decision Tree model can predict shrimp prices with an accuracy of 88.89%. The most influential factors in determining prices are weather conditions and feed prices. A web-based prediction system was also developed using PHP and MySQL to facilitate users in accessing price predictions interactively. This research is expected to assist farmers and traders in making better business decisions, optimize inventory management, and improve the efficiency of the vaname shrimp supply chain in the local market.