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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Hanny Handayani Sucinta
Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Computer Science & IT Control & Systems Engineering

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Penerapan Algoritma Holt-Winters Exponential Smoothing Untuk Estimasi Dan Naïve Bayes Untuk Klasifikasi Produksi Kelapa Sawit Hanny Handayani Sucinta; Tedy Setiadi
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 4 (2023): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i4.265

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.
Co-Authors Tedy Setiadi