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Implementation of Simple Exponential Smoothing and Weighted Moving Average in Predicting Netflix Stock Prices Sadewa, Bima; Safwandi, Safwandi; Fajriana, Fajriana
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.708

Abstract

This study aims to develop a stock price prediction system for Netflix using the Simple Exponential Smoothing and Weighted Moving Average methods and evaluate the accuracy of both methods. The system provides future stock price estimates based on historical data and includes evaluation metrics such as Mean Absolute Error and Mean Absolute Percentage Error. The implementation results show that SES achieved an MAE of 4.40 and a MAPE of 1.08%, while WMA resulted in an MAE of 8.65 and a MAPE of 2.11%. These findings indicate that SES is more effective in predicting stock prices with lower error rates, particularly for stable historical data. In contrast, WMA is more responsive to short-term trends but less accurate overall. Based on the results, SES is recommended as the developed system's primary method for stock price prediction.