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All Journal Jurnal Statistika dan Matematika (Statmat)
Rahmatuloh, Alam
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Forecasting Food Industry Enterprises in Ciamis Using Holt Winter Linear Trend Method Permana, Irfan; Rahmatuloh, Alam
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 8 No 1 (2026)
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v8i1.55211

Abstract

The food industry sector in Ciamis Regency plays an important role in driving regional economic growth and employment. Understanding its future trend is essential for supporting policy formulation and industrial development strategies. To predict the number of food sector businesses in Ciamis Regency, this study uses the Holt-Winters Linear Trend method. The number of food industry enterprises has shown fluctuating and declining patterns in recent years, raising the question of how accurately the Holt-Winters Linear Trend method can predict future non-seasonal trends. This study provides a new application of the Holt-Winters Linear Trend method for forecasting non-seasonal industrial data at a regional level, an area rarely explored in previous research on small-scale industries. The method was implemented in Python, and performance was evaluated using MAE, MSE, RMSE, MAPE, and R². The forecast shows that the number of food industry enterprises will reach 92 units in 2026, 77 in 2027, 89 in 2028, 75 in 2029, and 86 in 2030, with an accuracy of 93.40%. For future studies, ensemble forecasting is recommended, with related variables such as labor numbers and production value added to enhance method performance.
Co-Authors Permana, Irfan