PENGGUNAAN PREDIKSI AKURASI FORECASTING MENGGUNAKAN METODE ARIMA DAN HOLT-WINTERS PADA PENJUALAN (STUDI EMPIRIS PADA PT. KARUNIA ALAM SEGAR TAHUN 2020-2024)

Abstract

This study aims to compare the forecasting accuracy of the ARIMA and Holt-Winters methods in predicting sales at PT. Karunia Alam Segar for the period 2020–2024. A descriptive quantitative approach was employed using secondary data consisting of monthly sales records. The analysis was carried out using Microsoft Excel, with model accuracy evaluated through MAPE (Mean Absolute Percentage Error), MAD (Mean Absolute Deviation), and RMSE (Root Mean Squared Error). Prior to forecasting, data validity and reliability were tested using SPSS. The results indicated that the data were valid (r > 0.3) and reliable (Cronbach’s Alpha = 0.843). The ARIMA method produced forecasts with a sharp increase trend, but yielded a high error rate (MAPE > 100%), indicating poor accuracy. In contrast, the Holt-Winters method provided more stable and accurate predictions, with MAPE values ranging from 8% to 10%. Therefore, Holt-Winters is considered the more effective forecasting method for supporting PT. Karunia Alam Segar’s sales planning and distribution strategies. This research highlights the importance of selecting appropriate forecasting methods based on data characteristics and demonstrates the practicality of using Microsoft Excel for business data analysis. The results are validated and can serve as a reliable reference for strategic decision-making.