Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal EKUITAS (Jurnal Ekonomi dan Keuangan) Engineering, Mathematics and Computer Science Journal (EMACS)
Nanang Suryadi
Brawijaya University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mathematics

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CAPITAL STRUCTURE CATALYST: CONNECTING FINANCIAL LITERACY, INNOVATION, PROFITABILITY FOR VENTURE GROWTH Andarwati; Nanang Suryadi; Rizka Zulfikar
EKUITAS (Jurnal Ekonomi dan Keuangan) Vol 9 No 3 (2025): September
Publisher : Sekolah Tinggi Ilmu Ekonomi Indonesia (STIESIA) Surabaya(STIESIA) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24034/j25485024.y2025.v9.i3.7202

Abstract

This study investigated the impact of financial literacy, innovation, and profitability on the performance of new ventures, focusing on the mediating role of capital structure. Addressing a sample of 287 new ventures in East Java, Indonesia, this study employed the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach to analyze the relationships among key constructs. The findings revealed that innovation and profitability significantly influenced capital structure, which had a strong positive effect on firm performance.  The innovation had a direct impact on performance, while financial literacy and profitability did not show significant direct effects. Among the indirect effects, only innovation had a significant impact on performance through capital structure, reinforcing its strategic importance. The results of this study suggest that innovation, more than financial acumen or short-term profitability, plays a central role in shaping financial strategies that enhance new venture outcomes. The findings contributed to the entrepreneurial and financial management literature by integrating financial and non-financial competencies into a comprehensive model of entrepreneurial and financial management. This study also provided policymakers, educators, and practitioners with practical insights on how to strengthen the sustainability of new ventures through targeted innovation support and strategic financial structuring.
Mapping the Evolution of AI Chatbots in Indonesia (2021-2025): A PRISMA-Based Systematic Literature Review on Applications, Technologies, and Impacts Antonius Felix; Arta Moro Sundjaja; Julius Sutrisno; Nanang Suryadi
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 8 No. 1 (2026): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v8i1.14942

Abstract

The rapid development of artificial intelligence has accelerated the adoption of chatbots in organizations in Indonesia. But there is no systematic synthesis of the development of this technology in Indonesian context. This research provides a systematic review of the development and implementation of AI chatbots in Indonesia in 2021–2025, with the aim of filling the research gap related to sectoral applications, technological trajectories, and contextual challenges. A systematic literature review was conducted following the PRISMA 2020 guidelines on the Scopus, Google Scholar and arXiv databases to collect 257 initial records. After duplicate removal and a multi-step screening process, 16 high-quality studies were included in the final synthesis. Thematic analysis identified four main findings: (1) AI Chatbots are found in higher education, healthcare, banking, public services, fintech, e-commerce, and SMEs; (2) The technology has evolved from rule-based approaches (AIML, TF-IDF) to machine learning (Seq2Seq LSTM, Rasa+IndoBERT) and the latest large language model integration (GPT-3.5, Vertex AI); (3) Reported impacts include improved user satisfaction (SUS scores 80.1), operational efficiency, and 24/7 service availability; and (4) Existing challenges include accuracy in Indonesian language processing, complexities in system integration, data privacy issues, and varied levels of digital literacy. This review is the first systematic mapping of Indonesia’s AI chatbot landscape and makes evidence-based recommendations for the development of locally-adapted, culturally-sensitive models. Results show that future chatbot development should emphasize Indonesian language datasets and hybrid architectures that combine automation and human oversight.
Co-Authors Andarwati Antonius Felix Arta Moro Sundjaja Julius Sutrisno Rizka Zulfikar