A Time-Series Data Analysis about the Historical Population of the Philippines using 12-point Moving Average Forecasting
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)
(2022), pp. 1-5
Ashley L. De Jesus
a
,
Ace C. Lagman
a
,
Bea Glennel B. Lee
a
,
Katherine Mega F. Lopez
a
,
Ramir R. Ramirez
a
,
Maria Vicky S. Solomo
a
,
Darren Joshua A. Villarama
a
a FEU Institute of Technology
Abstract: One of the world's most serious challenges is the exponential expansion of the population. The Philippines is included in this category of "less developed countries." Moreover, the said country's population expansion is unstoppable. With at least three newborns born per minute, the country has one of the greatest population growth rates. Consequently, the researcher's objective is to use a machine-learning algorithm to forecast the possible Philippine population growth for the upcoming year. Employing Knowledge Discovery in Database (KDD) as the step-by-step process in determining solutions and answering each of the research questions of the study.With this, the researchers were able to forecast data using time series data analysis about the historical populations of the Philippines utilizing a 12-point moving average. Based on the accuracy performance of the model, the algorithm can be used as a reliable source and was considered a good fit with a 90.27% accuracy.