Claim Missing Document
Check
Articles

Found 5 Documents
Search

The Role of Emotional Intelligence in Enhancing Employee Engagement Among Generation Z Suyanto Suyanto; Rachmad Ilham; Adiba Fuad Syamlan
JUMBIWIRA : Jurnal Manajemen Bisnis Kewirausahaan Vol. 4 No. 1 (2025): April : Jurnal Manajemen Bisnis Kewirausahaan
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/jumbiwira.v4i1.2724

Abstract

This study explores the role of emotional intelligence in enhancing employee engagement among Generation Z within the creative industry in Surabaya, Indonesia. As digital natives, Gen Z employees seek emotional connection, purpose driven work, and psychologically safe environments. Using a qualitative case study approach, data were collected through in depth, semi structured interviews with ten participants and analyzed using thematic analysis. The findings reveal three dominant themes: empathetic leadership fosters psychological safety, frequent emotional feedback strengthens interpersonal connections, and purpose driven roles enhance intrinsic motivation and engagement. These insights highlight the generational uniqueness of Gen Z and suggest that emotional intelligence is not only a personal asset but a strategic organizational capability. This study provides practical implications for leadership development, HR practices, and organizational culture aimed at improving engagement and retention among younger employees.
The Impact of Cryptocurrency Adoption on Personal Financial Management Strategies Among Generation Z Slamet Abdul Muslikh; Adiba Fuad Syamlan; Anisaul Hasanah
JUMBIWIRA : Jurnal Manajemen Bisnis Kewirausahaan Vol. 4 No. 1 (2025): April : Jurnal Manajemen Bisnis Kewirausahaan
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/jumbiwira.v4i1.2726

Abstract

This study explores the impact of cryptocurrency adoption on personal financial management (PFM) strategies among Generation Z. As digital natives, Generation Z is increasingly integrating cryptocurrencies into their financial routines, yet their financial literacy levels vary significantly. Employing a qualitative literature review methodology, this research analyzes recent academic publications to examine how generational characteristics such as digital fluency, risk tolerance, and social media influence moderate the relationship between crypto usage and financial behaviors like budgeting, saving, and debt management. The findings reveal a dual effect: while cryptocurrency can enhance financial autonomy and portfolio diversification, it also increases the risk of impulsive and speculative behaviors among less financially literate users. This research underscores the importance of developing targeted financial education programs that incorporate both digital and behavioral components. The study contributes theoretically to behavioral finance and innovation diffusion models, and offers practical recommendations for educators and policymakers seeking to improve financial outcomes for Generation Z in a rapidly evolving digital economy.
Pengaruh Disiplin dan Kepuasan Kerja Terhadap Kinerja Karyawan di Departemen Rotto Cast PT. Langgeng Buana Jaya Gresik: Penelitian Muhammad Hikamush Shofi; Umar Burhan; Adiba Fuad Syamlan
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 1 (Juli 2025 -
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i1.1800

Abstract

Kajian ini memiliki sasaran untuk menelaah besaran dampak yang ditimbulkan oleh kedisiplinan dan kepuasan kerja mempengaruhi performa karyawan pada Departemen Rotto Cast PT. Langgeng Buana Jaya Gresik. Metode penelitian ini menerapkan metode pendekatan kuantitatif. Proses akuisisi data untuk kajian ini dilaksanakan dengan metode distribusi kuesioner kepada 111 orang Karyawan Departemen Rotto Cast PT. Langgeng Buana Jaya Gresik. Studi ini mengaplikasikan metodologi kuantitatif yang memanfaatkan analisis regresi linier berganda. Partisipan dalam riset ini berjumlah 111 orang, dengan proses perolehan data yang memanfaatkan instrumen angket. Pengujian data dieksekusi melalui penerapan serangkaian tes asumsi klasik, yang terdiri dari uji normalitas, multikolinearitas, heteroskedastisitas, autokorelasi, serta linearitas, dengan bantuan piranti lunak Statistical Package for the Social Sciences (SPSS) versi 25.0. Temuan dari analisis mengindikasikan bahwa secara bersamaan, Disiplin Kerja dan Kepuasan Kerja memberikan kontribusi positif serta signifikan pada Performa Karyawan di Departemen Rotto Cast PT. Langgeng Buana Jaya Gresik. Lebih lanjut, pengujian secara individual menemukan bahwa Disiplin Kerja mempunyai dampak yang positif juga signifikan terhadap Performa Karyawan. Variabel Kepuasan Kerja juga terbukti memberikan pengaruh konstruktif dan nyata atas Performa Karyawan. Maka karena itu, implikasi dari temuan riset ini adalah sebuah rekomendasi bagi pihak manajemen perusahaan untuk senantiasa mengoptimalkan Disiplin Kerja serta Kepuasan Kerja demi mendukung elevasi Performa Karyawan pada Departemen Rotto Cast PT. Langgeng Buana Jaya Gresik.
The Effect of Teamwork, Work Motivation, and Work Discipline on Employee Performance at PT. Berkah Kawan Setya M. Mafudz; Umar Burhan; Adiba Fuad Syamlan
GEMILANG: Jurnal Manajemen dan Akuntansi Vol. 5 No. 1 (2025): Jurnal Manajemen dan Akuntansi
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/gemilang.v5i1.2913

Abstract

This study aims to analyze the influence of teamwork, work motivation, and work discipline on employee performance at PT. Berkah Kawan Setya, a medium-sized construction company. This study used a quantitative approach with a survey method, where data was collected through questionnaires distributed to 47 employees. Data analysis was conducted using multiple linear regression to determine the contribution of each independent variable to employee performance. The results showed that all three independent variables—teamwork, work motivation, and work discipline—have a positive and significant influence on employee performance. Of these, work discipline exerts the most dominant influence, followed by teamwork and work motivation. The coefficient of determination (R²) of 81.8% indicates that the variation in employee performance can be explained by these three behavioral factors, with the remainder influenced by other variables outside the model. These findings emphasize the importance of developing a disciplined, collaborative work environment that sustainably motivates employees. In the context of construction companies facing the challenges of dynamic teamwork and tight project targets, a human resource development strategy focused on behavioral aspects is crucial. This research provides empirical insights for HR management in designing policies that can increase productivity and support project success. Recommendations for companies include strengthening a culture of discipline, building strong team synergy, and providing incentives and rewards to enhance employee motivation.
Artificial Intelligence in Financial Forecasting : Enhancing Accuracy and Strategic Planning in Financial Management Sulistiani Sulistiani; Adiba Fuad Syamlan; Bustanul Ulum
Brilliant International Journal Of Management And Tourism Vol. 5 No. 2 (2025): June : Brilliant International Journal Of Management And Tourism
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/bijmt.v5i2.4455

Abstract

This study explores the implementation of Artificial Intelligence (AI) technologies in financial forecasting, aiming to improve prediction accuracy and enhance strategic financial decision-making. Traditional forecasting methods, such as ARIMA and linear regression, often fall short in modeling complex, nonlinear financial data, especially in volatile markets. In response, this research investigates the comparative performance of machine learning (ML), deep learning (DL), and hybrid AI-big data models. A qualitative exploratory approach was adopted, involving a systematic literature review and semi-structured interviews with financial practitioners and experts. The analysis revealed that hybrid models integrating Random Forest with big data analytics achieved the highest predictive accuracy (93.2%) and operational adaptability. LSTM models also demonstrated strong performance in handling time-series data but were limited by their lack of interpretability. Compared to traditional models, AI-based approaches significantly reduced prediction errors and offered real-time responsiveness, aligning with the dynamic needs of financial environments. The findings support the hypothesis that AI technologies can bridge the gap between accurate forecasting and strategic financial planning. However, challenges such as high computational requirements and low model transparency persist. Therefore, the study concludes that while AI models present a transformative potential for financial forecasting, successful implementation requires balancing model performance with organizational capabilities and regulatory considerations. These insights provide valuable guidance for financial managers and policymakers seeking to adopt AI-driven forecasting systems in increasingly complex and data-rich financial landscapes.