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All Journal Jurnal Darma Agung Journal of Scientech Research and Development Inkubis: Jurnal Ekonomi dan Bisnis
Winotoatmojo, Hugo Prasetyo
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences

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EVALUASI STRATEGI INVESTASI PADA PASAR MODAL DIGITAL DAN CRYPTOCURRENCY PADA MANAJEMEN KEUANGAN PERUSAHAAN Setyawan, Antonius Ary; Winotoatmojo, Hugo Prasetyo
JURNAL DARMA AGUNG Vol 32 No 2 (2024): APRIL
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Darma Agung (LPPM_UDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/ojsuda.v32i2.4163

Abstract

Artikel ini bertujuan untuk mengevaluasi strategi investasi pada pasar modal digital dan Cryptocurrency dalam konteks manajemen keuangan perusahaan. Metode literatur review digunakan untuk menyelidiki berbagai pendekatan investasi yang relevan dan hasil evaluasi dari strategi-strategi tersebut. Dengan fokus pada investasi dalam aset digital dan Cryptocurrency, artikel ini menggambarkan berbagai strategi yang telah digunakan oleh perusahaan dalam mengelola portofolio keuangannya. Dengan mempertimbangkan karakteristik unik dari pasar modal digital dan Cryptocurrency, penulis mengevaluasi keefektifan strategi-strategi tersebut dalam menghasilkan keuntungan, mengelola risiko, dan memaksimalkan nilai perusahaan. Hasil literatur review menyoroti tantangan dan peluang yang terkait dengan investasi dalam aset digital, serta faktor-faktor yang perlu dipertimbangkan oleh manajer keuangan dalam pengambilan keputusan investasi. Artikel ini memberikan wawasan yang berguna bagi praktisi keuangan dan manajer perusahaan yang tertarik untuk memahami lebih lanjut tentang strategi investasi dalam pasar modal digital dan Cryptocurrency. Dengan demikian, artikel ini dapat menjadi panduan bagi perusahaan dalam mengembangkan pendekatan investasi yang sesuai dengan tujuan keuangan mereka di era digital ini.
ENVIRONMENTAL IMPACT OF CRYPTOCURRENCY MINING: SUSTAINABILITY CHALLENGES AND SOLUTIONS Winotoatmojo, Hugo Prasetyo; Lazuardy, Samuel Yesua; Arland, Fabian; Setyawan, Antonius Ary
Journal of Scientech Research and Development Vol 6 No 1 (2024): JSRD, June 2024
Publisher : Ikatan Dosen Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56670/jsrd.v6i1.312

Abstract

The rapid growth of cryptocurrencies over the past 14 years has led to increased deep-level mining activities. This research aims to explore the environmental impacts resulting from the surge in crypto mining and proposed solutions to mitigate these impacts. Cryptocurrencies, gaining popularity as alternative investments and global payment tools, have significantly boosted crypto mining activities. However, the increasing number of transactions requiring computer validation has resulted in adverse consequences for the environment, particularly in terms of substantial energy consumption. Literature review and systematic analysis were conducted to comprehend the environmental impact of crypto mining, focusing on major cryptocurrencies such as Bitcoin, Ethereum, and others. The analysis highlights that crypto mining, especially Bitcoin, requires a significant amount of electricity, leading to a substantial carbon footprint and broad environmental repercussions. Proposed solutions to address the environmental impact of crypto mining include the use of renewable energy sources such as solar and wind power, enhancing the efficiency of specialized mining devices (ASICs), and exploring more energy-efficient consensus mechanisms like Proof of Stake (PoS) compared to the currently utilized Proof of Work (PoW). Reducing redundancy in blockchain technology has also been identified as a crucial step in minimizing unnecessary energy consumption. However, this research has limitations concerning data consistency, a comprehensive understanding of overall environmental impacts, and continuous technological changes in the crypto world. Therefore, future research should focus on developing more efficient consensus mechanisms, effective policy frameworks and governance, as well as real-world implementation studies to evaluate the sustainability solutions proposed.
AI Disclosure, ESG Performance, and Tobin’s Q in Southeast Asian Banking Winotoatmojo, Hugo Prasetyo; Meiryani, Meiryani; Handoko, Bambang Leo; Setyawan, Antonius Ary
Inkubis : Jurnal Ekonomi dan Bisnis Vol. 8 No. 4 (2026): INKUBIS Jurnal Ekonomi Dan Bisnis
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/inkubis.v8i4.494

Abstract

Background: Banks increasingly disclose AI-related activities, but disclosure does not establish actual implementation or realized outcomes. Evidence remains limited regarding whether AI disclosure is associated with ESG performance and whether ESG performance subsequently has valuation relevance in Southeast Asian banking. Objective: This study examines the associations among AI disclosure, ESG performance, and Tobin’s Q. Methods: A balanced panel of 1,230 bank-year observations covering 205 banking entities in 10 Southeast Asian countries from 2020 to 2025 was analyzed using bank and country-year fixed effects with bank-clustered standard errors. Robustness checks included lagged specifications, alternative variable definitions, ESG-pillar models, country exclusions, and cluster bootstrap analysis of the indirect association. Results: AI disclosure was positively associated with contemporaneous ESG performance (β = 0.0139, p = 0.006; within R² = 0.007), with significant associations for social (β = 0.0181, p = 0.004) and governance (β = 0.0096, p = 0.018) performance. However, the disclosure–ESG association was not significant in lagged or one-year-ahead specifications. AI disclosure was not consistently associated with Tobin’s Q, and the bootstrap confidence interval for the indirect association included zero. Conclusion: AI disclosure is associated with ESG performance only contemporaneously and does not provide consistent evidence of valuation relevance through ESG. The findings support a cautious interpretation of AI disclosure as a potential signal and underscore the need for verifiable, outcome-linked reporting.
Co-Authors Arland, Fabian Bambang Leo Handoko, Bambang Leo Hendraningrat, Akbar Ramadhan Lazuardy, Samuel Yesua Meiryani, Meiryani Setiawati, Jovita Grace Setyawan, Antonius Ary