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All Journal Aptisi Transactions on Management International Transactions on Artificial Intelligence (ITALIC)
Susetyono, Eko
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science

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Foundations for AI Driven Communication Models Qualitative Analysis of Indonesian Language Adaptation E-Commerce Sunarya, Po Abas; Prabowo, Dimas Aditya; Angel, Mary; Fitriawati, Nora; Fernando, Erick; Susetyono, Eko; Madani, Muchlishina
International Transactions on Artificial Intelligence Vol. 3 No. 2 (2025): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i2.798

Abstract

In the rapidly evolving digital economy, effective communication between sellers and customers on e-commerce platforms plays a pivotal role in shaping user experience and satisfaction. This study explores the adaptation of the Indonesian language within these interactions, focusing on the linguistic styles, usage patterns, and communication challenges faced by sellers and customers. Employing a qualitative descriptive approach, data were collected from direct conversations and product descriptions on leading Indonesian e-commerce platforms. Findings reveal a dominant use of semi-formal and informal language styles, enhanced by abbreviations, emojis, and popular digital jargon, which collectively foster a sense of familiarity and responsiveness. However, balancing language standardization with the demands for fast and engaging communication remains a significant challenge. The results underline the critical need for communication models that can adapt to the dynamic nature of digital discourse while maintaining clarity and politeness. This research lays the groundwork for developing intelligent communication systems powered by artificial intelligence, which can effectively interpret and generate contextually appropriate language in e-commerce settings. The insights gained here offer valuable foundations for future work in creating AI-driven tools aimed at enhancing digital customer engagement and satisfaction through culturally and linguistically aware communication strategies.
AI Adoption Barriers in SMEs Analyzing Through the Technology Organization Environment TOE Framework Syahidun; Susetyono, Eko; Adiwijaya, Alfri; Madani, Muchlisina; Mustafa Kareem, Yasir
APTISI Transactions on Management (ATM) Vol 9 No 3 (2025): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/h6qyfk21

Abstract

Artificial Intelligence (AI) has become a key driver of innovation, improving efficiency, decision-making, and competitiveness in businesses worldwide. However, the adoption of AI tools among Small and Medium Enterprises (SMEs), especially in developing countries like Indonesia, remains limited. This study aims to explore the barriers hindering AI adoption in SMEs in Indonesia using the Technology Organization Environment (TOE) framework. A survey was conducted among Indonesian SMEs across various sectors to capture their perceptions regarding AI implementation. The survey focused on technological, organizational, and environmental factors that influence AI adoption. The findings reveal that technological barriers, such as high implementation costs and system complexity, are significant challenges for SMEs. Organizational barriers, including limited digital literacy, a lack of skilled workforce, and resistance to change, also hinder AI adoption. Furthermore, environmental barriers like insufficient government support, regulatory uncertainty, and low market pressure constrain SMEs' adoption readiness. This study extends the TOE framework to the context of AI adoption in SMEs in developing economies. Addressing the identified barriers is essential for accelerating digital transformation and enabling SMEs to leverage AI for sustainable growth in the digital economy.
Co-Authors Adiwijaya, Alfri Angel, Mary Erick Fernando B311087192 Fitriawati, Nora Madani, Muchlishina Madani, Muchlisina Mustafa Kareem, Yasir Po Abas Sunarya Prabowo, Dimas Aditya Syahidun