ANALISIS PERAMALAN PRODUKSI TANAMAN KELAPA SAWIT MENGGUNAKAN METODE ARIMA PADA PTPN KEBUN SUKAMAJU

The Indonesian palm oil industry plays an important role in the economic and social sectors by making a significant contribution to national income. This research aims to address the need for accurate production forecasting to manage the challenges of the palm oil industry and develop accurate ARIMA models, collect them, and optimize management operations. This research uses a combination type of research (mixed method) with the ARIMA (Autoregressive Integrated Moving Average) method to predict palm oil production at PTPN Kebun Sukamaju, a subsidiary of KSO PTPN III (Persero) in West Java. The data used is secondary data from 2016 to 2023, with a focus on monthly production figures. This research involves model identification, parameter estimation, diagnostic checks, and forecasting, using R-Studio software. The results of data analysis show that the best model is the ARIMA(1,1,3)(1,0,1) model[12]. Forecasting results show a decline in PTPN Kebun Sukamaju's palm oil production with a MAPE value of 12.49%. Forecasting results using the ARIMA(1,1,3)(1,0,1)[12] model provide insight for comprehensive managerial decision making.

Keywords: Production Forecasting, ARIMA, Operational Management