Implementasi Sistem Pengambilan Keputusan Pembelian Saham di Indonesia berdasarkan Kinerja Berbasis Web

Abstract

Stock purchases represent certificates of ownership in a company that are sold to the public. Making a stock purchase requires careful decision-making due to the large number of stock options available. One of the methods used is the trend following method, which can provide profit opportunities. However, calculations are still often done manually, which takes a lot of time to determine which stocks meet the criteria. Currently, there is no system that helps calculate the number of suitable stocks in Indonesia, which would otherwise save time and effort in identifying stocks that align with the trend following method. This research uses unstructured interviews, secondary data from the yfinance API, and literature review. The system is developed using the Python programming language for processing stock data and utilizes the Flask microframework to create a web application that is accessible and user-friendly. The result of this research is a decision support web application that meets users’ needs for selecting stocks from a large dataset of Indonesian stocks. The system calculates, sorts, and categorizes the stocks based on whether or not they meet the criteria. The conclusion of this research is that the system successfully provides stock calculation results that meet the criteria, aiding decision-making in selecting potentially profitable stocks. The system can be run via a web interface that is easy to use and understand, helping users analyze large volumes of stock data more efficiently and faster than manual methods.