Design of Database and Screener for Indonesian Stocks Fundamental Analysis

Abstract

The growth of retail investors in Indonesia has increased significantly, rising from 1.6 million in 2017 to over 12 million in 2024. Despite this upward trend, many investors particularly beginners still face challenges in performing efficient fundamental analysis. Manual and unstructured evaluation of financial metrics such as), price-to-earnings ratio (P/E), earnings per share (EPS, price-to-book ratio (P/B), return on equity (ROE), net income, debt-to-equity ratio (D/E), and cash flow remains common. This study proposes the development of a MySQL-based database system and screener preset that automates financial data management and stock filtering using stored procedures. The designed screener effectively integrates key financial analysis criteria and enables systematic, fast, and accurate stock selection. The results demonstrate the potential of the system to serve as a technical foundation for smarter stock analysis tools and to support data-driven investment decision-making in the Indonesian capital market.