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Optimal: Jurnal Ekonomi dan Manajemen
Published by Pusat Riset dan Inovasi Nasional
ISSN : 29624444     EISSN : 29624010     DOI : 10.55606
Core Subject :
OPTIMAL: Jurnal Ekonomi dan Manajemen berfokus pada penerbitan artikel berkualitas tinggi yang didedikasikan untuk semua aspek penelitian, masalah, dan perkembangan terbaru di bidang Ilmu Manajemen. Topik dalam Jurnal ini berkaitan dengan aspek apapun dari manajemen, namun tidak terbatas pada topik berikut : Manajemen Sumberdaya Manusia , Manajemen Keuangan, Manajemen Pemasaran, Manajemen Sektor Publik, Manajemen Operasional, Manajemen Rantai Pasokan, Corporate Governance, Etika Bisnis, Akuntansi Manajemen dan Pasar Modal dan Investasi. Jurnal ini terbit 1 tahun 4 kali (Maret, Juni September dan Desember)
Arjuna Subject : -
Articles 619 Documents
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Pertumbuhan Organik vs Anorganik: Perspektif Strategis dalam Menciptakan Keunggulan Kompetitif Muhamad Erwin Kurniawan; Syufriadi Ibrahim; Suparno Suparno; Saparuddin Mukhtar
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 2 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i2.6460

Abstract

In an increasingly competitive and rapidly evolving global marketplace, growth is no longer an option but a necessity for organizational survival and success. Companies must choose between various growth pathways—organic, inorganic, or hybrid—each offering unique advantages and trade-offs. This study explores the strategic role of these growth strategies in fostering sustainable competitive advantage. Employing a systematic literature review, the research analyzes how organizations align internal capabilities with external opportunities to pursue growth strategies that respond effectively to dynamic market conditions. Organic growth supports innovation, brand consistency, and cultural continuity, while inorganic growth facilitates rapid expansion and access to critical assets. Hybrid strategies, integrating both modes, enable firms to balance long-term development with short-term agility. The findings highlight that strategic fit, absorptive capacity, and organizational flexibility are essential for executing growth strategies successfully. This paper offers a conceptual synthesis that informs strategic decision-making and contributes to advancing the theoretical discourse on corporate growth.
Integrasi Pelayaran Perintis (Pioneer Shipping) dan Tol Laut untuk Mengoptimalkan Return Cargo di Indonesia Wawan Rudi Berlianto; Augustriandi Augustriandi; Suparno Suparno; Saparuddin Mukhtar
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 2 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i2.6465

Abstract

Indonesia’s Sea Toll Program was established to reduce regional price disparities and improve maritime connectivity across its archipelagic landscape. While outbound cargo distribution has expanded significantly, return cargo utilization remains low, averaging only around 31–33% over recent years. This inefficiency indicates a systemic gap in the national logistics framework, particularly the lack of integration between Sea Toll operations and pioneering sea transportation services that serve smaller, remote ports. Using Strategic Cooperative and Strategic Entrepreneurship frameworks, this study develops a conceptual model that unifies these systems through synchronized routing, digital platform integration, and local actor empowerment. Secondary data from government reports and logistics performance evaluations are used to examine institutional fragmentation and technological barriers. A practical example from the Saumlaki port highlights how route coordination and the involvement of cooperatives as cargo aggregators can improve backhaul efficiency. The study recommends strengthening SITOLAUT as an open logistics platform, upgrading infrastructure at small ports, and creating multi-stakeholder governance mechanisms. The proposed framework offers not only logistical improvements but also a policy roadmap for enhancing regional economic participation, reducing inequality, and building a sustainable maritime logistics ecosystem.
The Role of Chatbots in Enhancing Tourist Engagement: A Contextual Study of Bali Anak Agung Gede Wijaya
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 2 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i2.6467

Abstract

Bali, a globally recognized tourism destination, is actively integrating digital technologies to improve visitor experiences, with chatbots emerging as a key interface for enhancing tourist engagement. This study explores how chatbots function within Bali’s tourism ecosystem, focusing on their ability to deliver real-time assistance, personalized communication, and sustained interaction throughout the travel journey. Chatbots are found to play a strategic role in shaping tourist satisfaction and loyalty, yet their deployment in Bali is marked by uneven access, infrastructural limitations, and cultural considerations that affect user acceptance. Challenges such as limited digital readiness among small tourism enterprises and the need for culturally aligned chatbot interactions underscore the importance of localized solutions. The findings emphasize that the successful implementation of chatbot technologies in Bali depends on linguistic inclusivity, trust-building design, and supportive digital policies that enable broader adoption across the tourism sector.
Analisis Kemampuan Kerja Karyawan Berdasarkan Faktor Pengalaman Kerja, Lingkungan Kerja, Penghargaan dan Pemberian Soft Skill pada PT. Makmur Karya Persada Makassar Azwar Wijaya Syam; Sudirman Sudirman; Muh. Ridwan
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6496

Abstract

This study aims to find out and analyze the work ability of employees based on the factors of Work Experience, Work Environment, Awards and Soft Skills and which variables are dominant in PT Makmur Karya Persada Makassar. The type of research used is quantitative analysis, In research the analysis method used is regression analysis, in this case the regression used is multiple regression analysis using spss software version 26. Based on the results of the study, it shows that the variables of Soft Skills, Awards, work environment, and work experience together have a significant influence on employee performance and have a very strong influence on employee performance. The Soft Skill  variable partially has a dominant effect on employee performance At PT. Makmur Karya Persada Makassar This means that to achieve more effective employee performance based on organizational goals and expectations, employees must be given good training and education in order to improve technical abilities and skills based on the functions and main tasks of an employee.
Effectiveness of Using AI-Based Chatbots in Increasing Customer Engagement Sutantri Sutantri
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 2 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i2.6516

Abstract

This study examines the effectiveness of AI-based chatbots in enhancing customer engagement across various industries. Against the backdrop of increasing digital transformation, the research explores how chatbots influence key metrics such as response time, customer satisfaction, and conversion rates, while identifying implementation challenges and success factors. Through a systematic analysis of recent case studies and empirical data, the study reveals that well-designed chatbots can improve customer satisfaction by 18 percentage points and reduce response times by 99.6%, though limitations persist in handling complex queries and ensuring data privacy. The findings highlight the importance of anthropomorphic design, omnichannel integration, and balanced human-AI collaboration in optimizing chatbot performance. Practical implications suggest that businesses should prioritize transparent data policies, continuous model training, and user-centric conversation flows to maximize engagement. The study contributes to the growing body of knowledge on AI-driven customer service by synthesizing actionable insights from diverse sectors, including retail, banking, and healthcare.
Moderasi Kecerdasan Buatan dalam Hubungan Perkembangan Mahasiswa dengan Peningkatan Prestasi dan Kepuasan Belajar di STIE Cendekia Karya Utama Semarang Yudho Purnomo
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 4 No. 4 (2024): Desember : Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v4i4.6525

Abstract

This study aims to analyze the role of artificial intelligence (AI) implementation as a moderating variable in the relationship between student development and the implications of AI use on improving academic outcomes and student learning satisfaction. The focus of the study was directed at students of the Economics Study Program at STIE Cendekia Karya Utama Semarang with a total of 38 respondents selected through the Cross Section/Isedentil sampling technique, namely data collected only at a certain time. The method used is a quantitative approach with moderation regression analysis using the help of smart PLS software. The results of the study indicate that student development does not have a significant effect on academic outcomes and learning satisfaction. In addition, the implementation of AI has been shown to positively moderate the relationship, which means that the use of AI strengthens the influence of student development on improving academic performance and learning satisfaction. These findings recommend optimizing the use of AI-based technology in the learning process to improve the quality of higher education, especially in the field of economics.
Financial leadership today deman Financial Leadership : Navigating Change and Driving Growth in the Modern Era Dwiki Priyandono; Mochamad Syafii; Rachmad Ilham
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6539

Abstract

Financial leadership today demands far more than managing budgets or ensuring compliance it requires shaping strategy, driving technology adoption, and aligning financial decisions with long-term stakeholder value. This article examines how the role of the CFO has evolved into a central force behind business transformation. It outlines four concrete capabilities now essential for financial leaders: reallocating capital dynamically in response to market shifts, leading enterprise-wide digital initiatives like AI-driven forecasting and automation, embedding ESG metrics directly into investment decisions and risk models, and influencing non-financial KPIs such as innovation return and customer lifetime value. Traditional leadership models that focus on variance analysis and quarterly reporting fail to equip CFOs for real-time, cross-functional leadership. Drawing from recent academic literature, this article demonstrates that companies with CFOs who embrace data fluency, experimentation, and sustainability outperform peers in agility and resilience. It calls for executive development programs that incorporate training in digital tools, ESG analytics, and strategic scenario planning. These changes are critical not just to redefine finance functions, but to equip organizations for growth and stability in volatile, tech-driven markets.
AI in Financial Forecasting : Improving Accuracy and Strategy M.Mahdi Alatas; Bilgah Bilgah; Eka Putri Hanyani; Resti Yulistria
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6541

Abstract

Financial forecasting faces growing challenges due to market volatility and the inadequacy of traditional models like ARIMA and linear regression in handling non-linear, high-frequency financial data. Artificial intelligence (AI), particularly models such as long short-term memory (LSTM) networks and transformer-based systems, has demonstrated superior performance in tasks like predicting S&P 500 index movements and assessing corporate credit risk in real time. These models not only improve accuracy but also enable strategic applications—for instance, integrating live sentiment data from financial news to adjust portfolio allocations within milliseconds. AI systems have also been used by investment firms to simulate recession scenarios and guide capital reserve strategies. However, adoption remains hindered by issues such as the “black box” nature of deep learning, inconsistent data quality, and concerns over algorithmic bias. As AI continues to evolve, its value lies not just in forecasting precision but in supporting adaptive, transparent, and forward-looking financial management
The Role of Artificial Intelligence in Risk Management for Financial Institutions Muhammad Tomy Mubarroq; Suharto Suharto; Mochamad Syafii
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6544

Abstract

Artificial intelligence (AI) is changing how financial institutions manage risk, as traditional methods struggle to keep up with fast-moving threats and growing data complexity. AI technologies like machine learning and natural language processing are now used to improve credit scoring, detect fraud faster, predict market risks, and automate compliance tasks. This study explores how these tools are being applied to make risk management more accurate and efficient. Findings show that using new types of data—such as mobile usage or online behavior—helps assess credit for those without formal histories, AI reduces false fraud alerts significantly, and compliance work becomes faster with automated document reading. Still, challenges remain: some AI models are too difficult to explain to regulators, biased results have raised fairness concerns, and older systems in many banks can’t support AI in real time. These issues highlight the need for clearer models, stronger safeguards, and better technology systems. Institutions are encouraged to train staff on AI oversight, use tools to check for bias, and partner with regulators to safely test new systems before full use.
Smart Finance : Leveraging Technology for Optimal Financial Decision-Making Nurul Afifah; Mochamad Syafii; Firdaus Indrajaya Tuharea
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6549

Abstract

The complexity of financial decision-making has intensified in the digital era due to data saturation, market volatility, and the inability of conventional models to respond to real-time and non-linear dynamics. Addressing these challenges requires the integration of intelligent systems capable of adapting to evolving financial environments. Smart finance, which combines artificial intelligence, machine learning, big data analytics, blockchain, and automation, offers transformative potential across financial services. This study synthesizes scholarly findings from 2019 to 2024 across five domains: AI-based modeling, robo-advisory applications, behavioral finance integration, decentralized finance (DeFi), and real-time risk analytics. Results indicate substantial gains in efficiency, accuracy, and personalization, yet also reveal persistent challenges, including algorithmic opacity, ethical concerns in data use, and regulatory ambiguity. Advancing smart finance demands development in explainable AI, hybrid advisory systems, and inclusive, adaptive regulation for decentralized infrastructures. The scope of the analysis is limited to peer-reviewed academic literature published in English, excluding industry reports and grey literature.

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