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Cost of Production, Cost of Operation, and Net Sales to Net Profit Oktaviano, Benny; Dian Sulistyorini Wulandari; Ade Priyani
Indonesian Journal of Economic & Management Sciences Vol. 2 No. 1 (2024): February 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijems.v2i1.7991

Abstract

This research aimed to assess the impact of production costs, operating costs, and net sales on the net income of metal and comparable manufacturing companies listed on the Indonesia Stock Exchange during the period 2016–2020, whether individually or collectively. The data collection employed a purposive sampling method. The findings revealed that production costs had a partial impact on net income, whereas operating costs exhibited an influence on net income, while net sales did not. Collectively, the variables of production costs, operating costs, and net sales exerted a significant effect on net income. The R2 test indicated a value of 0.359. These results substantiate that production costs, operational costs, and net sales jointly contribute to the net income of metal and similar manufacturing companies on the Indonesia Stock Exchange for the 2016-2020 period, accounting for 35.9%. This implies that profit in this study is influential, while the remaining 64.1% is influenced by other factors not considered in this research
Rasio Leverage dan Aktivitas dalam Mempengaruhi Profitabilitas Perusahaan Farmasi Hidayat, Taufik; Dasman, Sunita; Oktaviano, Benny; Wahyuningsih, Mesela Nurhana
Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Vol 7 No 1 (2024): Article Research Volume 7 Number 1, January 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi Al-Washliyah Sibolga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36778/jesya.v7i1.1537

Abstract

This study aims to analyse the effect of Debt to Asset Ratio (DAR), Debt to Equity Ratio (DER), and Total Asset Turnover (TATO) on Return on Equity (ROE) in the context of corporate financial performance. DAR measures the extent to which the company's assets are financed with debt, DER measures the company's capital structure, while TAT measures how efficient the company is in generating revenue from its assets. ROE is a metric that reflects a company's level of profitability compared to shareholders' equity. This study uses a quantitative approach in which the data is in the form of annual financial reports of Pharmaceutical Companies for the period 2017 - 2021. This study aims to determine, examine and analyse the conditions of Debt to Asset Ratio (DAR), Debt to Equity Ratio (DER), and Total Asset Turnover (TATO) on Return on Equity (ROE). The sampling technique used purposive sampling. This type of research uses quantitative descriptive analysis with data analysis techniques using panel data regression analysis. The results showed that DAR and TATO had a significant positive effect on ROE, while DER did not affect ROE. From the research results, the company should pay more attention to capital and asset turnover to be more effective in increasing profits.
The Role of Artificial Intelligence in Collaborative Green Supply Chain Management: Impact on Company Performance and Moderation of Top Management Commitment Bernando, Franky Okto; Ray, Erick Lauren; Oktaviano, Benny
Jurnal Logistik Indonesia Vol. 9 No. 2: Oktober 2025
Publisher : Institut Ilmu Sosial dan Manajemen Stiami

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study explores the growing interest in big data and Artificial Intelligence (AI) while addressing the gap in research on AI's role in Collaboration within Green Supply Chain Management (CGSCM) and its impact on Firm Performance (FP). Integrating AI and assessing Top Management Commitment (TMC) as a moderating factor, a moderated mediation model was constructed using data from 152 Indonesian manufacturing firms. The results show that AI positively influences CGSCM and FP, with CGSCM acting as a mediator between AI and FP. Additionally, TMC enhances the positive relationship between AI and CGSCM, strengthening this connection at higher TMC levels. Conversely, TMC moderates the link between AI and FP, reducing its strength at lower TMC levels. These findings provide valuable insights for supply chain and logistics managers, offering guidance on implementing AI to promote collaboration in sustainable supply chains and improve firm performance.