PREDIKSI PENDAPATAN DARI PENJUALAN BERDASARKAN DATA HISTORIS DENGAN MENGGUNAKAN METODE ELASTIC NET
DOI:
https://doi.org/10.29407/kgb28a75Abstract
Penelitian ini bertujuan untuk memprediksi total pendapatan hasil panen bawang merah berdasarkan data historis jumlah panen dan harga per kilogram menggunakan metode Elastic Net. ElasticNet dipilih karena mampu menggabungkan keunggulan dari regularisasi L1 (Lasso) dan L2 (Ridge), yang efektif dalam mengatasi overfitting dan meningkatkan akurasi model. Dataset yang digunakan terdiri dari 36 data penjualan bawang merah dari tahun 2014 hingga 2022. Hasil evaluasi menunjukkan bahwa model mampu memberikan prediksi dengan tingkat akurasi yang baik, dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 15.07% dan nilai koefisien determinasi (R²) sebesar 0.8374. Dengan hasil tersebut, metode Elastic Net terbukti dapat digunakan secara efektif untuk memodelkan dan meramalkan pendapatan penjualan berbasis data historis di bidang pertanian.
Keywords:
elastic net, historis, regresi##plugins.themes.default.displayStats.downloads##
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