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All Journal Jurnal Ilmiah Raflesia Akuntansi
Nosperiani Halawa
STIE Pembangunan Tanjung Pinang
Economics, Econometrics & Finance

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Penerapan Teknologi Berbasis Sistem Informasi Terhadap Penggunaan Transaksi Pembayaran QRIS Dalam Meningkatkan Efisiensi Operasional Shella Shella; Elisa Elisa; Epehulisa Br Ginting; Everlin Everlin; Nosperiani Halawa; Shelia Shelia; Zona Kharisma Sinta
Jurnal Ilmiah Raflesia Akuntansi Vol. 11 No. 1 (2025): Jurnal Ilmiah Raflesia Akuntansi
Publisher : Politeknik Raflesia Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53494/jira.v11i1.823

Abstract

This study aims to analyze the opportunities and challenges in implementing QRIS as a digital payment method for MSMEs in Tepi Laut Tanjungpinang. With the increasing trend of cashless transactions, this research explores the benefits, obstacles, and optimization strategies for QRIS adoption among small and medium enterprises. The research method used is a qualitative approach through direct observation and interviews with several MSMEs that have adopted QRIS, such as Pisang Kembung Viral, Es Jeruk Kiamboy, MK Dimsum, Teh Tarik Malaysia Brother, and Corndog Tarik Lumer. The phenomenon underlying this research is the rising adoption of digital payments among MSMEs, which still faces various challenges, such as customer preference for cash and technical transaction issues. The findings indicate that QRIS offers multiple benefits for MSMEs, particularly in enhancing operational efficiency, speeding up transactions, and facilitating financial record-keeping. However, challenges persist, including technical constraints and administrative fees that may reduce business profits. The conclusion of this study highlights the importance of customer education, selecting QRIS service providers with lower administrative costs, and improving infrastructure to ensure smooth digital transactions. As recommendations, MSMEs are encouraged to actively promote QRIS usage among customers, collaborate with digital financial service providers, and leverage social media to expand cashless transactions.
Menganalisis Penggunaan Teknologi AI dalam Personalisasi Pengalaman Customer Yunda Syafira; Andini Kartika Dewi; Berliana Kristiana N.S; Norazlina Norazlina; Nosperiani Halawa; Sri Susanti
Jurnal Ilmiah Raflesia Akuntansi Vol. 11 No. 1 (2025): Jurnal Ilmiah Raflesia Akuntansi
Publisher : Politeknik Raflesia Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53494/jira.v11i1.848

Abstract

The development of digital technology, especially Artificial Intelligence (AI), has significantly transformed the business and customer service landscape in the Industry 4.0 era. This study aims to analyze the application of AI technology in customer experience personalization and its impact on customer loyalty and satisfaction. This research employs a qualitative method with a literature review as the primary technique. The data used is secondary, sourced from credible references such as Google Scholar and peer-reviewed journals. The findings show that AI, through machine learning and Natural Language Processing (NLP), enables companies to understand and tailor services to individual customer preferences. Machine learning algorithms allow for the collection and analysis of customer behavior data to provide more accurate and relevant recommendations, increasing sales conversion and customer loyalty. NLP supports more natural customer interactions through chatbots and virtual assistants, enhancing responsiveness and service quality. However, challenges such as data privacy, information security, and algorithmic bias remain key obstacles in AI implementation. To address these issues, companies are advised to comply with data protection regulations such as GDPR and ensure transparency in AI-driven decision-making. In conclusion, the application of AI in customer experience personalization provides a competitive advantage for companies by improving operational efficiency, customer satisfaction, and loyalty, but it must be balanced with strict privacy and security policies.
Co-Authors Andini Kartika Dewi Berliana Kristiana N.S Elisa Elisa Epehulisa Br Ginting Everlin Everlin Norazlina Norazlina Shelia Shelia Shella Shella Sri Susanti Yunda Syafira Zona Kharisma Sinta