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Demand Analysis for Large Animal and Poultry Meat in Indonesia: An ARDL Perspective Muksalmina, Muksalmina; Nasir, Muhammad; Sartiyah, Sartiyah
Ekonomikalia Journal of Economics Vol. 2 No. 2 (2024): October 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/eje.v2i2.202

Abstract

This study examines the growing demand for large livestock and poultry meat in Indonesia, reflecting changing consumption patterns and economic growth. However, this phenomenon faces challenges such as price fluctuations between provinces, declining per capita income, and supply-demand gaps that affect access to and consumption of animal protein. Utilizing panel data from 34 provinces covering the period from 2015 to 2022 and employing an Autoregressive Distributed Lag (ARDL) model, this study analyzes the short- and long-run relationships in meat demand. The results indicate that in the short run, meat prices and per capita income significantly influence demand, while tuna prices have no noticeable effect. In the long run, meat prices, per capita income, and fish prices as substitutes affect meat demand. This study contributes to the development of the livestock sector in Indonesia, provides information for farmers to plan production, and advises the government to educate the public about protein sufficiency and conduct market operations to stabilize prices and maintain meat availability. The findings are expected to help fulfill the current and future demand for meat from large livestock and poultry in Indonesia.
Artificial Intelligence in Islamic Finance: Forecasting Stock Indices with Neural Prophet Muksalmina, Muksalmina; Idroes, Ghadamfar Muflih; Maulana, Aga
Indatu Journal of Management and Accounting Vol. 2 No. 2 (2024): December 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v2i2.232

Abstract

Ensuring financial system stability is paramount, especially in markets guided by Sharia principles, where investor confidence and adherence to ethical standards play critical roles. The ability to accurately forecast stock movements within this framework not only supports informed investment decisions but also strengthens the overall stability of financial markets. This research employs the innovative Neural Prophet model to predict Islamic stock indices in Indonesia with remarkable accuracy and depth. The model demonstrates its capability not only in accurately forecasting trends but also in detecting subtle fluctuations within three Islamic stock indices: the Jakarta Islamic Index (JII), the Jakarta Islamic Index 70 (JII70), and the Indonesia Sharia Stock Index (ISSI). Visual representations highlight the model's adaptability and advanced foresight, surpassing traditional models. The significance of this research lies in its potential to enhance the precision of stock index predictions, particularly for Islamic stocks, offering stakeholders deeper insights. The model's effectiveness spans both stable and volatile market conditions, making it a valuable tool for informed financial decision-making. Accurate forecasts aid in risk management and support well-informed investment decisions in fluctuating markets, thereby contributing to financial system stability.
Credit Card Fraud Detection Through Explainable Artificial Intelligence for Managerial Oversight Muksalmina, Muksalmina; Syahyana, Ahmad; Hidayatullah, Ferdy; Idroes, Ghalieb Mutig; Noviandy, Teuku Rizky
Indatu Journal of Management and Accounting Vol. 3 No. 1 (2025): June 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v3i1.301

Abstract

As digital payment systems grow in volume and complexity, credit card fraud continues to be a significant threat to financial institutions. While machine learning (ML) has emerged as a powerful tool for detecting fraudulent activity, its adoption in managerial settings is hindered by a lack of transparency and interpretability. This study examines how explainable artificial intelligence (XAI) can enhance managerial oversight in the deployment of ML based fraud detection systems. Using a publicly available, simulated dataset of credit card transactions, we developed and evaluated four ML models: Logistic Regression, Naïve Bayes, Decision Tree, and Random Forest. Performance was assessed using standard metrics, including accuracy, precision, recall, and F1-score. The Random Forest model demonstrated superior classification performance but also presented significant interpretability challenges due to its complexity. To fill this gap, we applied SHAP (SHapley Additive exPlanations), a leading method for explaining the outputs of the Random Forest model. SHAP analysis revealed that transaction amount and merchant category were the most influential features in determining the risk of fraud. SHAP plots were used to make these insights accessible to non-technical stakeholders. The findings underscore the importance of XAI in promoting transparency, facilitating regulatory compliance, and fostering trust in AI-driven decisions. This study offers practical guidance for managers, auditors, and policymakers seeking to integrate explainable ML tools into financial risk management processes, ensuring that technological advancements are balanced with accountability and informed human oversight.
Membangun Minat Investasi Melalui Pelatihan Simulasi Pasar Modal bagi Mahasiswa di Kantor IDX Banda Aceh Muksalmina, Muksalmina; Hidayatullah, Ferdy; Syahyana, Ahmad
Jurnal Solusi Masyarakat Dikara Vol 5, No 2 (2025): Agustus 2025
Publisher : Yayasan Lembaga Riset dan Inovasi Dikara

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

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan literasi keuangan dan pemahaman mahasiswa Universitas Ubudiyah Indonesia terhadap investasi saham melalui pelatihan berbasis simulasi pasar modal. Selama tiga hari, peserta diberikan pemahaman komprehensif mengenai konsep dasar investasi, strategi diversifikasi portofolio, serta manajemen risiko. Metode yang digunakan meliputi penyampaian materi interaktif, diskusi kelompok, serta kompetisi simulasi investasi dengan data pasar riil. Hasil pelatihan menunjukkan peningkatan signifikan dalam pengetahuan dan keterampilan peserta. Skor rata-rata post-test meningkat sebesar 40% dibanding pre-test. Simulasi investasi yang dilakukan peserta juga mencerminkan pemahaman yang baik terhadap strategi portofolio, di mana total return portofolio mencapai +1,4% meskipun terdapat saham berkinerja negatif. Selain itu, 75% peserta menyatakan minat untuk membuka rekening saham riil, dan 90% merasa puas dengan metode pelatihan yang diberikan. Kegiatan ini tidak hanya berhasil membangun pemahaman dasar tentang investasi, tetapi juga menumbuhkan minat serta kepercayaan diri mahasiswa untuk terlibat langsung dalam pasar modal. Sebagai tindak lanjut, dibentuk rencana pembentukan Kelompok Studi Pasar Modal (KSPM) serta kolaborasi berkelanjutan dengan BEI Banda Aceh. Dengan pendekatan yang sistematis dan aplikatif, kegiatan ini diharapkan menjadi fondasi dalam membangun budaya literasi keuangan yang berkelanjutan di lingkungan kampus.
Understanding E-Money Preferences Among Students: A Case Study at FEBI UIN Ar-Raniry, Banda Aceh, Indonesia Muksalmina, Muksalmina; Ahmadsyah, Israk; Dianah, Azimah
Grimsa Journal of Business and Economics Studies Vol. 1 No. 1 (2024): January 2024
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjbes.v1i1.11

Abstract

As digital financial transactions continue to gain traction globally, understanding the factors that influence the adoption of electronic money (e-money) is crucial. This research paper delves into the behavioral aspects behind the use of e-money within a specific academic community. In a quantitative study carried out at Ar-Raniry State Islamic University's Faculty of Islamic Economics and Business (FEBI), we investigated the impact of utility, convenience, and security on students' interest in selecting e-money as their preferred payment method. The randomized sample of 97 students represented the faculty's diverse population. Our findings emphasize the critical roles of utility and convenience in shaping students' interest in e-money adoption, with attributes like speed, efficiency, and practicality significantly driving their embrace of electronic payment solutions. The research underscores the importance of designing e-money systems that prioritize utility and convenience to attract users, particularly in educational settings, while also providing insights for policymakers and financial institutions seeking to promote digital financial inclusion.
Exploring Organizational Citizenship Behavior to Identify Job Performance Based on Perspectives Organizational and Psychological Empowerment in the Hospitality Sector Muksalmina, Muksalmina; Hidayatullah, Ferdy; Syahyana, Ahmad; SI, Sari Raudhatul Jannah
Indatu Journal of Management and Accounting Vol. 3 No. 2 (2025): December 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v3i2.348

Abstract

In an era of global competition and digital transformation, improving human resource performance has become a strategic factor for the hospitality industry, which is highly dependent on service quality. This study aims to analyze the role of organizational citizenship behavior (OCB) in mediating the influence of perceived organizational support and psychological empowerment on the job performance of hospitality employees. A quantitative approach was used, with a survey method targeting star-rated hotel employees in Banda Aceh City, Indonesia. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to test the direct and indirect relationships between latent variables. The results showed that perceived organizational support and psychological empowerment had a positive and significant effect on job performance, both directly and through the mediation of OCB. OCB was found to play an important role in strengthening the relationship between psychological factors and job performance, particularly through voluntary behaviors such as helping colleagues, maintaining the organization’s image, and improving service effectiveness. These findings confirm that superior performance in the hospitality industry is not only determined by managerial systems, but also by the psychological and social aspects of employees. In the context of Aceh Province, which has distinctive religious values and social norms, organizational citizenship behavior becomes an important mechanism for building professionalism and work ethics in line with Sharia principles. This study provides practical implications for hotel management to improve organizational support, strengthen psychological empowerment, and create a collaborative work culture oriented toward service quality.