Penerapan Metode Holt-Winters untuk Memprediksi Produksi Biji Kopi Arabica Lintong Nihuta - Arina Prima Silalahi; Tamado Simon Sagala; Laura Sridevi Sihombing; Harlen Gilbert Simanullang (METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi, 2026)
Arabica coffee bean production in Lintong Nihuta fluctuates every month, requiring a method to predict future production volumes. Accurate predictions can aid production planning and decision-making. This study aims to predict Arabica coffee bean production using the Holt-Winters multiplicative method, which can capture trends and seasonal patterns in time series data. The data used are 60 monthly production data points from January 2021 to December 2025. The analysis process begins with determining the initial values of the level, trend, and seasonal components, followed by a smoothing process using parameters α = 0.4, β = 0.45, and γ = 0.35. Model evaluation was performed using the Mean Absolute Percentage Error (MAPE) using 2025 data as the evaluation data. The evaluation results show a MAPE value of 13.12%, indicating that the model has a good level of accuracy. The prediction results show that Arabica coffee bean production in 2026 is expected to fluctuate, with the highest predicted value in December at 75,297.15 kg and the lowest in May at 36,737.38 kg. Therefore, the Holt-Winters multiplicative method can be used to predict Arabica coffee bean production in the Lintong Nihuta District in the future.