Time Series Forecasting for Issuance of Alien Employment Permits by Nationality in the Philippines Using Holt-Winters Method

To sustain competition in a work environment, it is essential that goods and services be available all the time and that they meet customer satisfaction. In the Philippines, some of the workforces of foreign investments are personnel who are citizens of their country. The condition necessitates the issuance of employment permit to foreign nationals by the Bureau of Labor under the Department of Labor and Employment (DOLE). It is possible to forecast the estimated number of permits to be issued by the DOLE using Triple Exponential Smoothing (TES) also known as Holt-Winters Method, a time series forecasting technique. It is chosen TES and has advantages when it comes to adjusting to changing trends and seasonal components. This study used this forecasting method based on the lowest forecast error values. Time series forecasting demand plot data shows fluctuating demand over time. In this paper, using Microsoft Excel, the Holt-Winters method was conducted using a statistical technique. The performance has been evaluated based on predictive accuracy and the analysis, Holt-Winters model provides the best performance in terms of the lowest error factors. Dataset of Alien Employment permit by nationality is available at Open Data Philippines portal. Study revealed that there is an annual average growth of 2.58%, 2,97% and 1.60% in the issuance of permit for American, British and Chinese nationals respectively.