Penerapan Model ARIMAX Untuk Prediksi Penjualan Toko Kiranashoop15 Di Shopee - Setiawan, Agus; Sulistiyanto, Bayu; Ariessanti, Hani Dewi; Munawar (Computer Science and Information Technology, 2026)
Transactions on the Shopee marketplace generate large volumes of records that can be turned into a basis for sales forecasting. This study applies an Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) approach to forecast the monthly total sales of the Kiranashoop15 store while identifying the exogenous factors that most influence the model. Data were drawn from the Shopee Seller Centre income report for January 2020 to May 2025, originally 11,142 order-level records, which were cleaned and aggregated into 65 monthly observations. The series was split chronologically into 52 training months and 13 testing months, with standardized exogenous variables covering product price, discounts, vouchers, cashback, shipping cost, and marketplace fees. Model parameters were searched through a grid search minimizing the Akaike Information Criterion (AIC). The selected model, ARIMAX(2,1,4), produced an AIC of 1203.78. On the test set the model achieved an MAE of Rp51,825, RMSE of Rp62,484, and MAPE of 0.461%, while the Ljung-Box test (p-value 1.00) confirmed white-noise residuals. Product Original Price contributed the largest relative share (68.87%), followed by Campaign Cost (22.13%). The six-month forecast (June-November 2025) indicates total sales ranging from Rp14.20 million to Rp15.22 million per month with a stable tendency. These findings confirm that ARIMAX is a suitable tool for marketplace sales forecasting.