MUHAMAD NUR ROZIKIN, 7211414163 (2019) PENGARUH STRUKTUR MODAL, PROFITABILITAS, LIKUIDITAS, DAN INVESTMENT OPPORTUNITY SET (IOS) TERHADAP KUALITAS LABA. Under Graduates thesis, Universitas Negeri Semarang.

PDF (PENGARUH STRUKTUR MODAL, PROFITABILITAS, LIKUIDITAS, DAN INVESTMENT OPPORTUNITY SET (IOS) TERHADAP KUALITAS LABA) - Published Version Restricted to Repository staff only Download (2MB) | Request a copy

Abstract

Rozikin, Muhamad Nur. 2019. "The Influence of Capital Structure, Profitability, Liquidity and Investment Opportunity Set (IOS) on Earnings Quality". Final Project. Accounting Department. Faculty of Economics. Universitas Negeri Semarang. Advisor Drs. Fachrurrozie, M.Si. Keywords: Capital Structure, Profitability, Liquidity, Investment Opportunity Set (IOS), Earnings Quality. Earning quality refers refers to the amount of income that can be consumed without negative impact on companies ability to pay operational expenditure. Low earning quality occurs when the profit presented is not in accordance with the actual profit. It is based on several factors of the company that originated from ratio of financial reports published by management, such as capital structure, profitability, liquidity, and investment opportunity set (IOS). The study population included manufacturing companies listed on Indonesia Stock Exchange (IDX) during 2015-2017. This research used purposive sampling method by selecting 36 companies out of 154 populations so 108 unit analysis were obtained corresponding to predefined criteria. Data was analized both descriptively and inferenly using multiple linear regression. The results showed that liquidity measured by the current ratio and investment opportunity set (IOS) had a significant positive effect on earnings quality, capital structure calculated with leverage had a significant negative effect on earnings quality. Meanwhile, profitability proxied by ROE does not significantly influence the positive direction of earnings quality. This study obtained an Adjused R Square value of 0.338, which means that the dependent variable can be explained by the independent variable at 33.8% and the remaining 66.2% is explained by other variables outside the research model. further research is expected to add other variables such as company size, profit growth, accrual quality, information asymmetry, or use other measurements, to get better results as new information for companies, investors and other parties who need information.

Actions (login required)

View Item