Financial Ratio Prediction for Accounting Information System Using Holt-Winters Exponential Smoothing

Intan Dzikria (Universitas 17 Agustus 1945 Surabaya)
Muhammad Ikram Fahriono (Universitas 17 Agustus 1945 Surabaya)
Rayhan Rizaldi Hi Hukum (Universitas 17 Agustus 1945 Surabaya)
Muhammad Ferianto (Universitas 17 Agustus 1945 Surabaya)
Acxell Rizada Sudigto (Universitas 17 Agustus 1945 Surabaya)
Sigit Ananda Murwato (Universiti Tun Hussein Onn Malaysia)

Journal of Information Technology and Cyber Security
Vol. 4 No. 2 (2026): July

Financial ratio analysis serves as a vital tool for assessing organizational performance and supporting decision-making processes. This study developed an accounting information system featuring financial ratio prediction capabilities powered by the Holt-Winters Exponential Smoothing algorithm—a method capable of handling time-series data characterized by trends and seasonality. Functional testing demonstrated that the system operates according to design, achieving a 94% success rate. Prediction results varied in accuracy: the current ratio achieved a Mean Absolute Percentage Error (MAPE) of 8.3%, indicating a favorable prediction outcome. Conversely, the Return on Investment (ROI), Return on Equity (ROE), and debt-to-equity ratios yielded MAPE values exceeding 20%, signaling a need for improved accuracy. These findings suggest that the system can serve as a relevant analytical tool for financial management; however, further development is required, particularly regarding algorithm parameter optimization and the provision of higher-quality data.