Peramalan Stok Gula Merah dengan ARIMA dan Prediksi Biaya Distribusi menggunakan XGBoost

Authors

  • Ellok Sintha Maydiana Universitas Nusantara PGRI Kediri Indonesia
  • Patmi kasih Universitas Nusantara PGRI Kediri Indonesia
  • Muh Aris Saputra Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/4xk5p226

Abstract

Ketidakpastian persediaan stok barang dan fluktuasi biaya logistik distribusi memicu inefisiensi operasional pada sektor perdagangan gula merah. Penelitian ini bertujuan mengembangkan sistem manajemen penjualan terintegrasi menggunakan arsitektur hibrida dengan kerangka kerja Laravel dan React.js, serta layanan kecerdasan buatan berbasis Python. Metode peramalan stok dieksekusi melalui algoritma AutoRegressive Integrated Moving Average (ARIMA), sedangkan estimasi biaya pengiriman logistik menggunakan algoritma Extreme Gradient Boosting (XGBoost). Hasil pengujian komputasi peramalan murni ke depan (out-of-sample) dari model ARIMA(1,1,1) merekam tingkat kesalahan dinamis dengan Mean Absolute Percentage Error (MAPE) di rentang 32,29% hingga 61,52%, menjustifikasi kemampuan model dalam mendeteksi tren dasar persediaan. Sementara itu, model regresi XGBoost meraih akurasi Koefisien Determinasi (R2) memukau sebesar 95,5% dengan Mean Absolute Error (MAE) senilai Rp12.053,21. Kesimpulannya, integrasi sistem teknologi mutakhir ini terbukti andal menciptakan tata kelola anggaran berbasis data (data-driven).

Keywords:

ARIMA, biaya distribusi, gula merah, manajemen penjualan, XGBoost

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References

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Published

2026-07-20

Issue

Vol. 10 No. 1 (2026): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2026

Section

Articles

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How to Cite

Peramalan Stok Gula Merah dengan ARIMA dan Prediksi Biaya Distribusi menggunakan XGBoost. (2026). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 10(1), 68-75. https://doi.org/10.29407/4xk5p226