Prediksi Stok Tanaman Hidroponik dengan Artificial Intelligence: Ensemble Learning dengan Optimasi Evolusioner - Putu Bagus Adidyana Anugrah Putra; Septian Geges; Oktaviani Enjela Putri; I Made Bayu Artha Pratama (STEKOM PRESS, 2024)
Hydroponic plant cultivation is booming, but stock and sales are hard to predict. Poor prediction can cause farmers to overstock and lose money. This study suggests a framework that uses several machine learning models, including Linear Regression (LR), Random Forest (RF), Decision Tree (DT), and Extreme Gradient Boosting.