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Mandalika Journal of Business and Management Studies
Published by Yayasan Banu Haji Samsudin
ISSN : 30254116     EISSN : 30254116     DOI : 10.59613
Core Subject : Science,
Decision Sciences, Operations Research & Management
Jurnal ini merupakan sarana publikasi ilmiah untuk menyebarluaskan informasi berupa ilmu pengetahuan dan terlebih khususnya hasil penelitian hasil penelitian, jurnal ini juga menerima manuskrip hasil kajian pustaka dan laporan lainnya untuk dipublikasikan
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 73 Documents
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Good University Governance: Budget Accountability And The Demarcation Of Legal Risks In Public Universities Ari Yunus Hendrawan
Mandalika Journal of Business and Management Studies Vol 4 No 2 (2026): Mandalika Journal of Business and Management Studies
Publisher : Mandalika Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/mjbms.v4i2.492

Abstract

Good University Governance (GUG) constitutes a fundamental framework for ensuring financial accountability and legal compliance in public universities. Although previous studies have extensively examined financial accountability and internal control in higher education, limited attention has been devoted to the legal risk demarcation between procedural administrative errors and corruption offenses arising from dysfunctional treasury systems during institutional crises. This study addresses this gap by analyzing the implementation of the principles of segregation of duties and functional accountability while examining the legal boundaries between administrative maladministration and criminal liability in budget management within a public university postgraduate program during the 2018–2022 fiscal years. Employing a qualitative empirical juridical (socio-legal) case study, data were collected through semi-structured interviews with eleven key informants, organizational observations, and documentary analysis of forensic audit reports and state treasury records. The findings indicate that the prolonged dysfunction of officially designated treasury officers resulted in the informal delegation of financial responsibilities to contract-based staff, creating serious governance failures. These failures were manifested in manipulated financial documents, counterfeit official stamps, and double-funding practices involving personal bank accounts, demonstrating the existence of criminal intent rather than mere procedural irregularities. The novelty of this study lies in integrating Good University Governance with contemporary administrative and criminal law perspectives to establish a legal risk demarcation framework distinguishing maladministration from corruption offenses. The study contributes theoretically by extending governance-based legal accountability in public universities and practically by recommending mandatory cashless transactions, integrated digital payment systems, and stricter segregation of duties to strengthen financial accountability and prevent corruption.
Optimizing Financial Risk Management Through the Integration of Artificial Intelligence Machine Learning and Strategic Human Resource Management to Anticipate Financial Crises and Enhance Corporate Financial Stability Haris Aulia Rahman; Ardilla Ayu Kirana; Moh. Sholeh; M.Makhrus Ali; Joni Devitra
Mandalika Journal of Business and Management Studies Vol 4 No 2 (2026): Mandalika Journal of Business and Management Studies
Publisher : Mandalika Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/mjbms.v4i2.479

Abstract

This study examines how the integration of Artificial Intelligence (AI), Machine Learning (ML), and Strategic Human Resource Management (SHRM) can optimize financial risk management to anticipate financial crises and enhance corporate financial stability. The research employs a qualitative library research approach using primary and secondary data collected from books, peer-reviewed journals, scientific reports, and other relevant academic literature. Data were analyzed using content analysis to identify theoretical patterns, conceptual relationships, and emerging trends related to intelligent financial risk management. The findings indicate that AI and ML significantly improve financial forecasting, fraud detection, and risk prediction through advanced predictive analytics, while SHRM strengthens organizational capabilities by developing adaptive leadership, digital competencies, and strategic decision-making. The integration of these technological and organizational resources creates a comprehensive financial risk management framework that enhances organizational resilience and supports sustainable financial performance. The study concludes that combining AI, ML, and SHRM enables organizations to proactively manage financial uncertainty, improve crisis preparedness, and achieve long-term corporate financial stability in an increasingly dynamic business environment.
Penggunaan Media Sosial Untuk Meningkatkan Brand Merk Produk Loeky Rono Pradopo; Mulyana Chandra Hadiati; Supriyatno Supriyatno; Evi Dwi Nur Atika; Ayu Kurnisari
Mandalika Journal of Business and Management Studies Vol 4 No 2 (2026): Mandalika Journal of Business and Management Studies
Publisher : Mandalika Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/mjbms.v4i2.494

Abstract

Social media has become a strategic channel for companies to build and enhance brand merk produk amid increasingly intense market competition. This study aims to analyze the effect of five dimensions of social media usage—intensity of social media use (X1), quality of social media content (X2), user interaction (X3), trust in information (X4), and promotion effectiveness (X5)—on brand merk produk (Y). A quantitative approach with a survey design was employed, involving 103 respondents who are social media users and consumers of the product under study. Data were analyzed using Structural Equation Modeling with Partial Least Square (SEM-PLS) using SmartPLS version 4, through measurement model (outer model) evaluation, structural model (inner model) evaluation, and hypothesis testing using bootstrapping (5,000 resamples). The results show that the measurement model meets the criteria for good convergent validity and reliability (loading factor > 0.7; AVE > 0.5; Cronbach’s Alpha and Composite Reliability > 0.7), and adequate discriminant validity based on the Heterotrait-Monotrait Ratio (HTMT) criterion. The R-square value of 0.789 indicates that the five dimensions jointly explain 78.9% of the variance in brand merk produk, categorized as substantial. Hypothesis testing shows that intensity of social media use (β = 0.331; t = 3.925; p = 0.000) and promotion effectiveness (β = 0.381; t = 3.964; p = 0.000) have a positive and significant effect on brand merk produk, while quality of content, user interaction, and trust in information show no statistically significant effect at the 5% level. These findings indicate that a high intensity of social media use and effective promotion are the main drivers of brand merk produk improvement, so companies’ social media strategies should be focused on these two aspects.

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