FORECASTING KONSUMSI BARANG BARANG PADA STORAGE HOTEL DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE

Abstrak

In this era, hotel has storage as a storing space for every kind of Barangs. Barangs stored in the storage are Barangs being used for the needs of the staffs, also for the needs of hotel’s operational. The Barang consumption is running smoothly with resupply. However, there are often mistakes in resupplying the Barangs. For preventing those several mistakes, a reference is needed to be used for controlling the amount of Barangs arrival (monthly) with minding the amount of Barangs in the storage should be. The reference to be used is the forecast of the Barang consumption every month. Forecasting was being done with Autoregressive Integrated Moving Average (ARIMA) method. There are five steps needed to build the ARIMA model, such as plot identification, model identification, model estimation, choosing the best model, and prediction (forecast). The input variable to be used in this research is the rime series from the data of storage’s Barang consumption starts from January 2018 until October 2020, and the output variable is the result of the prediction of Barang consumption in the next period.