ANALYSIS OF ACCURACY LEVEL OF MOVING AVERAGE, PARABOLIC SAR AND CONVOLUTIONAL INDICATORS NEURAL NETWORK ON BUY AND SELL DECISIONS (Case study of shares of PT Bank Negara Indonesia, Tbk) - Axmal Fauza; Evi Noviaty (Jurnal Ekonomi, 2022)
The development of the global COVID-19 pandemic in the fourth quarter of 2021 was marked by the increase in global daily cases after the reopening in various countries and the emergence of Omicron as a new variant of concern. The banking sector is one of the main sectors supporting the Indonesian economy. As we enter the era of the industrial revolution 4.0, people see the capital market as a reliable source of income to increase their income. This is evidenced by the large number of foreign and local investors who invest their capital in the world capital market. The movement of stock prices on the Indonesian stock exchange is very volatile. This is a risk that must be borne by every investor, especially short-term investors. Many methods are used in predicting the stock price, one of which is by using technical analysis indicators such as the Moving Average and Parabolic SAR. In addition to using technical analysis in making investment decisions, investors can also use machine learning algorithmic indicators such as the Convolutional Neural Network. By using the tradingview website application and the AXMAL 1.0 mobile application in collecting data and also analyzing data on stock price movements of PT. Bank Negara Indonesia Tbk., it is obtained that the results of the Convolutional Neural Network indicator accuracy are greater than the Moving Average and Parabolic SAR indicators, which are 56.1% and also produce a higher return of 27.14% during the 2021 period, while the Parabolic SAR indicator produces an accuracy level which is the same as the Moving Average indicator, which is 33.3% but produces a positive return of 12.51% while the Moving Average indicator produces a negative return of-4.46%.