Journal of Artificial Intelligence and Digital Business
Vol. 5 No. 2 (2026): Mei-Juli

Pengaruh Prediksi Kebangkrutan Menggunakan Model Springate terhadap Harga Saham pada Perusahaan Makanan dan Minuman Terdaftar di Bursa Efek Indonesia Tahun 2020–2024

Ahmad Faruq (Universitas Pamulang)
Yanto Nius Gulo (Universitas Pamulang)



Article Info

Publish Date
30 Jun 2026

Abstract

This study aims to analyze the effect of financial ratios derived from the Springate bankruptcy prediction model, namely Working Capital to Total Assets, Earnings Before Interest and Taxes (EBIT) to Total Assets, Earnings Before Tax to Current Liabilities, and Sales to Total Assets, on stock prices. The research uses a quantitative associative approach with a population of food and beverage companies listed on the Indonesia Stock Exchange (IDX) during 2020–2024. Using purposive sampling, 11 companies were selected as the sample. Secondary data were obtained from annual financial reports and stock price data published by the IDX. Data analysis was conducted using multiple linear regression with EViews version 13. The results show that Working Capital to Total Assets does not significantly affect stock prices. Likewise, Earnings Before Interest and Taxes to Total Assets and Earnings Before Tax to Current Liabilities have no significant effect on stock prices. Sales to Total Assets is also not proven to significantly influence stock prices. These findings indicate that the financial ratios contained in the Springate model are not sufficient predictors of stock price movements in food and beverage companies listed on the IDX. Therefore, investors should consider other financial and non-financial factors when making investment decisions. This study contributes to the development of literature regarding bankruptcy prediction models and stock market performance in Indonesia.

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Journal Info

Abbrev

RIGGS

Publisher

Subject

Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

Description

Journal of Artificial Intelligence and Digital Business (RIGGS) is published by the Department of Digital Business, Universitas Pahlawan Tuanku Tambusai in helping academics, researchers, and practitioners to disseminate their research results. RIGGS is a blind peer-reviewed journal dedicated to ...