Profitability Reviewed from Capital Structure, Revenue Growth and Asset Management in Manufacturing Companies in the Cosmetics and Household Needs Sub-Sector on the Indonesia Stock Exchange - Ade Retno Wahyuni; Pipit Buana Sari; Cahyo Pramono (Universitas Dehasen Bengkulu, 2026)
This study aimed to analyze the effect of capital structure, revenue growth, and asset management on profitability in manufacturing companies in the cosmetics and household goods sub-sector listed on the Indonesia Stock Exchange. Capital structure was measured using the debt to equity ratio, asset management was measured using the total assets turnover ratio, and profitability was measured using the return on assets ratio. This study was conducted in 2026 and employed a quantitative approach with an associative method. The research population consisted of 9 companies, with a sample of 7 companies selected for analysis. The observation data covered the period from 2020 to 2024. Secondary data in the form of companies’ financial statements were obtained from www.idx.co.id. Panel data regression analysis was applied using EViews 9.0 software. The results of the analysis indicated that the Random Effect Model was selected as the appropriate regression model. The findings revealed that capital structure, revenue growth, and asset management, both partially and simultaneously, had a significant effect on corporate profitability. Capital structure had a negative effect, while revenue growth and asset management had positive effects on profitability. Asset management was identified as the most dominant variable influencing profitability. All proposed hypotheses (H1, H2, H3, and H4) were proven and accepted, as the research findings were consistent with the hypotheses. The coefficient of determination (adjusted R²) of 0.527 indicated that 52.7% of the variation in profitability was explained by capital structure, revenue growth, and asset management, while the remaining variation was explained by other factors not examined in this study. In addition, the strength of the relationship between the independent variables and the dependent variable was considered strong, with a correlation coefficient (R) of 0.754.