Article Per Year (5 Year)
p-Index From 2021 - 2026
1.686
P-Index
This Author published in this journals
All Journal CommIT (Communication & Information Technology) Binus Business Review ComTech: Computer, Mathematics and Engineering Applications Journal of Applied Engineering and Technological Science (JAETS) Engineering, Mathematics and Computer Science Journal (EMACS) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Arta Moro Sundjaja
Bina Nusantara University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
Chatbot Quality and Its Impact on User Satisfaction and Continuance Usage Intention in the Indonesian Banking Industry Angela Irena; Sabrina Tiffany; Tobias Benito Aripradono; Arta Moro Sundjaja
CommIT (Communication and Information Technology) Journal Vol. 20 No. 1 (2026): CommIT Journal (in press)
Publisher : Bina Nusantara University

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

Abstract

The research aims to investigate the role of chatbot quality in influencing user satisfaction and continuance usage intention within the Indonesian banking industry. The research is among the first to apply Expectation Confirmation Theory (ECT) to chatbot usage in the Indonesian banking industry and offers a novel integration of chatbot quality dimensions within the framework. A quantitative explanatory method is adopted, and a purposive sampling method is used to collect 347 valid responses via an online structured questionnaire. Data analysis is conducted using Partial Least Squares-Structural Equation Modeling (PLSSEM) with a focus on reflective-formative evaluation, bootstrapping for hypothesis testing, PLS-Predict for out-of-sample predictive performance, and Importance-Performance Analysis (IPMA) for managerial insights. The results show that chatbot quality significantly enhances both perceived usefulness and confirmation to subsequently reinforce user satisfaction and continuance usage intention. Satisfaction is identified as the strongest predictor of continuance usage. Meanwhile, chatbot disclosure does not have a significant impact on perceived quality, and it reflects the gap between transparency efforts and user perception. The observations underline the importance of designing chatbots that are responsive, context-aware, and linguistically adaptive specifically in the diverse communication landscape of Indonesia. The research contributes to the growing body of knowledge on AI-driven customer service technologies in emerging markets by offering practical implications for chatbot implementation in the financial sector. The identification of critical determinants of chatbot success also leads to the provision of insights for banks to enhance digital engagement, foster trust, and ensure long-term usage through optimized conversational experiences.
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 Abdinagoro, Sri Bramantoro Andika Pratama Angela Irena Antonius Felix Bahtiar S. Abbas Dery Remmy Lardo Ford Lumban Gaol Giovanka Savina Gladys Valentina Arisanto Julius Sutrisno Nanang Suryadi Nilo Legowo Ong Alexander Ang Ricky Adrian Gunawan Sabrina Tiffany Sarah Fatimah Thomas Hardianto Tobias Benito Aripradono Veronica Veronica Yudhi Kristianto Yuli Yuli