Prediksi Penyediaan Material Kwh Meter (Pasang Baru) Menggunakan Metode Exponential Smoothing

Abstrak

Efficient inventory management for KWH meter materials is essential to support new installation services at PT PLN (ULP Bumi Abung). Inaccurate forecasting may lead to overstock, increasing storage costs, or understock, which disrupts service performance. This study applies the Exponential Smoothing method to forecast material needs based on historical demand data. Forecasting was performed using manual calculations in Microsoft Excel and automated modeling in RapidMiner. The results show that Exponential Smoothing provides stable and sufficiently accurate predictions for upcoming material requirements. The forecasting output aids the company in optimizing inventory levels, reducing stock imbalance risks, and improving operational efficiency.

Keywords— Material forecasting, KWH meter, Exponential Smoothing, inventory.