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This UI program if it isn’t managed well so that can affect the insurance company performance and can make the company loss. One of the ways to know the development of this insurance claim for each month is that by forecasting the people who are interested in this insurance. The aim of this study is forecasting unemployment insurance claimants in IOWA, USA. This research uses ARIMA, NNETAR, Robus Exponensial Smooting, Theta Model, and α-Sutte Indicator forecasting method. The use of this method is intended to be compared the level of accuracy from various forecasting methods. To see the quality of the forecast, so that it will be used a comparison based on MSE score. The lower MSE Score, the better accuracy level that they have. The result of this study is α-Sutte Indicator is more appropriate in forecasting data unemployment insurance claim in IOWA. The accuracy level of α-Sutte Indicator is better if it is compared to any other methods.

IOWA Unemployment Insurance Claimants: A Comparison between α-Sutte Indicator and Other Forecasting Methods