Perbandingan Akurasi Metode ANN dengan FTS Model Chen, Cheng, dan Marcov Chain terhadap Peramalan Harga Penutupan Saham Zoom Video Communication
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Abstract
Stock price forecasting has become one of the important areas after the COVID-19 pandemic. This study aims to compare the accuracy of forecasting the closing price of Zoom Video Communication, Inc. shares using the Artificial Neural Network (ANN) Backpropagation and Fuzzy Time Series (FTS) methods with the Chen, Cheng, and Marcov Chain models. The data used in this study includes the closing price of shares from the period July 5, 2019 to January 4, 2024. Each method is evaluated using accuracy metrics such as RMSE, MSE, and MAPE. The results of the analysis show that ANN has a lower error rate than the FTS model, especially in predicting the closing price of Zoom Video Communication, Inc. The ANN method has proven to be more reliable in providing more accurate predictions.
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