Data Mining Menggunakan Multiple Regression untuk Prediksi Harga Saham Netflix
| Autor: | Rama Dona Ariyatma, Syahrul Fahmi |
|---|---|
| Jazyk: | indonéština |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Jurnal Saintekom, Vol 13, Iss 2, Pp 184-192 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2088-1770 2503-3247 |
| DOI: | 10.33020/saintekom.v13i2.419 |
| Popis: | Investing in the stock market is an important and fascinating endeavor, especially when we observe significant increases in certain stocks. Currently, Netflix stock is one of the rising stars and sought after by investors. However, along with the potential for high profits, there are certainly risks of losses that need to be anticipated. To mitigate these risks, an investor must make predictions about future stock prices. One method that can be used is data mining, a data processing technique used to discover patterns in data. In this study, data mining was conducted using the multiple regression algorithm to predict the future price of Netflix stock. Python and Jupyter Notebook were used as tools to process the data, which was collected from January 4, 2010, to March 30, 2023, totaling 3334 data points. After data processing, the model yielded a score of 0.99%, indicating a highly reliable model. Additionally, evaluation using RMSE resulted in a value of 3.73, and MAE had a value of 2.80, both derived from 1334 testing data points. With accurate prediction results and the evaluation conducted, an investor can use these findings as a reference when deciding whether to buy or sell Netflix stock. |
| Databáze: | Directory of Open Access Journals |
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