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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
Jurnal Elektronika dan Komputer
Vol 17
, No 2
(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. "Ensemble Learning," which combines these models, should yield more accurate and generalizable results than a single model. This framework is assessed using historical hydropo...
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Sistem Informasi Penjualan Toko Parfum Berbasis Website : (Studi Kasus : Toko Tunam8 Parfum)
Jurnal Elektronika dan Komputer
Vol 17
, No 1
(2024)
This research aims to design a website-based online store by utilizing a recommendation system with content-based filtering. The recommendation system is useful to help buyers get product suggestions that are in accordance with their preferences. The development method used in this research is the Waterfall model with the stages of needs analysis, design, program code generation, and testing. Researchers also use the UML model to help design the system and use the Laravel framework for website d...
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