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All Journal Journal of Artificial Intelligence and Digital Business
Ahmad Faruq
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering

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Pengaruh Likuiditas terhadap Struktur Modal pada Perusahaan MLBI yang Terdaftar di Bursa Efek Indonesia Tahun 2014 - 2024 Gulo, Yanto Nius; Faruq, Ahmad
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 1 (2026): Februari - April
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i1.6941

Abstract

This study aims to analyze the effect of liquidity on capital structure at PT Multi Bintang Indonesia Tbk, which is listed on the Indonesia Stock Exchange (IDX), during the period 2014–2024. The research approach used is a quantitative associative method by utilizing secondary data in the form of the company’s annual financial statements. The research population includes all financial data of PT Multi Bintang Indonesia Tbk over eleven years, which are also used as the research sample. Data processing was carried out using SPSS software version 27 through simple linear regression analysis. the results show that the correlation coefficient (R) is 0.791, indicating a strong relationship between the liquidity variable and capital structure. The coefficient of determination (R²) of 0.625 indicates that 62.5% of the variation in capital structure can be explained by liquidity, while the remaining 37.5% is influenced by other factors outside the research model. Partial hypothesis testing produces a liquidity regression coefficient of -3.104 with a significance level of 0.004, meaning that liquidity has a significant effect on capital structure. This negative relationship indicates that an increase in liquidity tends to be followed by a decrease in capital structure. these findings suggest that the level of liquidity plays an important role in corporate financing decision-making. Therefore, management needs to pay close attention to optimal liquidity management in order to achieve an efficient and sustainable capital structure. This study is expected to provide theoretical and practical contributions to the development of corporate financial policies.
Pengaruh Prediksi Kebangkrutan Menggunakan Model Springate terhadap Harga Saham pada Perusahaan Makanan dan Minuman Terdaftar di Bursa Efek Indonesia Tahun 2020–2024 Ahmad Faruq; Yanto Nius Gulo
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 2 (2026): Mei-Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i2.10056

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.
Co-Authors Yanto Nius Gulo