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The Influence of Return on Assets (ROA), Debt to Equity Ratio (DER), Current Ratio (CR), Debt to Asset Ratio (DAR) On Stock Returns in Food and Beverage Sector Manufacturing Companies Listed on The Indonesia Stock Exchange for The Period 2018 - 2022 Herlin Munthe; Novita Royana Marbun; Yara Ainy br Ginting; Kiki Hardiansyah Siregar
Jurnal Ekonomi, Bisnis & Entrepreneurship Vol. 18 No. 1 (2024): Jurnal Ekonomi, Bisnis & Entrepreneurship (e-Journal)
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat (P3M) STIE Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55208/tsfrj430

Abstract

This study seeks to examine the impact of Return on Asset (ROA), Debt to Equity Ratio (DER), Current Ratio (CR), and Debt to Asset Ratio (DAR) on Stock Return in manufacturing companies within the food and beverage industry sector listed on the Indonesia Stock Exchange from 2018 to 2022. The study will analyze the relationship between these variables both individually and simultaneously. The approach employed in this study is a quantitative methodology. From 2018 to 2019, 28 food and beverage industry production enterprises comprised 80 samples. This study utilized purposive sampling and employed various statistical tests, including the partial t-test, simultaneous F-test, classical assumption test, and adjusted R-square test. The test results indicate a significant relationship between Return on Assets (ROA) and Return on Sales (RS), as evidenced by the p-value of 0.003, which is less than the significance level of 0.05. (2) In the SPSS T-test, a sig value of 0.499>0.05 indicates no significant influence of DER on RS. (3) The results of the SPSS testing using the T-test show that the significance value is 0.484, more significant than 0.05. This condition indicates that CR does not have a significant influence on RS. (4) Based on the findings of the statistical significance test (p-value of 0.134>0.05), it may be inferred that DAR does not have a significant influence on RS. The calculated value of f, 4.664, is greater than the critical value of 2.49, and the significance level of 0.003 is less than the threshold of 0.05. Therefore, we can infer that the null hypothesis (H0) is rejected and the alternative hypothesis (Ha) is accepted. The Adjusted R Square value is 0.194, indicating that the independent variables can explain 19.4% of the variation in Y (RS). Other factors influence the remaining 80.6% of the variation.
Blockchain-Enabled Intelligent Platforms: Enhancing Trust and Transparency in Halal Food Kiki Hardiansyah Siregar; Tasriani Tasriani
Journal of Intelligent Systems and Information Technology Vol. 3 No. 2 (2026): July
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v3i2.279

Abstract

Indonesia's halal industry faces significant challenges in bridging the gap between 30 million products requiring mandatory halal certification and only 9.6–9.8 million products officially registered with BPJPH, compounded by 40% consumer skepticism toward halal claims due to a paper-based certification system vulnerable to forgery. Blockchain-enabled intelligent platforms are essential to enhance transparency and trust through real-time digital verification. To design and test a blockchain-based halal verification platform integrated with QR codes and intelligent information systems, enabling end-to-end tracking from producers to consumers, reducing certification fraud, and improving consumer trust and system efficiency. This study employs a quantitative-explanatory R&D approach to develop a three-tier system (frontend web/mobile, Python/SQL backend, blockchain simulation), tested for performance on 10,000–100,000 halal product datasets. Primary data (Likert-scale trust scores, response time, accuracy) and secondary data (BPJPH statistics) were analyzed using descriptive statistics and scalability simulations. Research Findings: The platform achieved 99.7% verification accuracy, 1.2–2.1 second response times, and a 0.3% error rate. Consumer trust scores improved from 3.1 to 4.3 (+39%), with 92% of users rating the system as "very user-friendly." The system scaled effectively to 100,000 datasets with CPU usage below 40%. Blockchain-enabled intelligent platforms effectively enhance consumer trust, certification transparency, and computational efficiency, supporting Indonesia's target of 100% mandatory halal certification by 2030–2035. This platform is ready for integration with BPJPH's ecosystem for national-scale UMKM and halal industries.