Penerapan Algoritma Holt-Winters Exponential Smoothing Untuk Estimasi Dan Naïve Bayes Untuk Klasifikasi Produksi Kelapa Sawit

Hanny Handayani Sucinta(1*), Tedy Setiadi(2),

(1) Universitas Ahmad Dahlan, Yogyakarta, Indonesia
(2) Universitas Ahmad Dahlan, Yogyakarta, Indonesia
(*) Corresponding Author

Abstract


This research optimizes oil palm production data in Kuantan Singingi Regency using Holt-Winters Exponential Smoothing and Naïve Bayes methods. With parameters alpha = 0, beta = 0.1, and gamma = 0.2, the estimation model successfully increases production in the upcoming months. Evaluation using MAPE shows estimation accuracy below 18%. The Naïve Bayes classification model achieves an accuracy of around 85%, indicating a good balance between accuracy and precision. This study provides a significant contribution to oil palm production planning and assists farmers and cooperatives in more efficient management.

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DOI: https://doi.org/10.30645/kesatria.v4i4.265

DOI (PDF): https://doi.org/10.30645/kesatria.v4i4.265.g263

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