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All Journal Madani: Multidisciplinary Scientific Journal
Mulyawati, Cindy
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Journal : Madani: Multidisciplinary Scientific Journal

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The Influence of Compensation and Motivation on the Performance of Grab Online Transportation Drivers in Palembang City Florensia, Erika; Mulyawati, Cindy; Hendrata, Florence; Martin, Alnov
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 12 (2026): January
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18074590

Abstract

This study aims to analyze the influence of compensation and service quality on the performance of Grab online transportation drivers in Palembang City. The increasingly intense competition in the online transportation industry requires companies to pay attention to driver welfare while maintaining service quality to ensure optimal performance. This research uses a quantitative approach with a survey method by distributing questionnaires to Grab drivers in Palembang City. The independent variables tested are compensation and service quality, while the dependent variable is driver performance. Data analysis is conducted using multiple linear regression. The results of this study are expected to show that adequate compensation and good service quality have a positive and significant effect on improving driver performance. This study provides practical implications for Grab management in formulating compensation strategies and improving service quality to support customer satisfaction and sustainable driver performance.
The Influence of Recommendation Systems and AI Chatbots on Customer Experience on Shopee Hendrata, Florence; Mulyawati, Cindy; Florensia, Erika
Madani: Jurnal Ilmiah Multidisiplin Vol 4, No 1 (2026): February 2026
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18616895

Abstract

The use of artificial intelligence technologies has become increasingly dominant in the e-commerceindustry, particularly through the implementation of recommendation systems and AI-based chatbots to enhance digital service quality. This study aims to analyze the influence of recommendation systems and AI chatbots on customer experience on the Shopee platform. The research employed a quantitative approach using a survey method involving 155 active Shopee users selected through purposive sampling. The research instrument consisted of 25 statement items that were proven to be valid and reliable. Data analysis was conducted using multiple linear regression with the assistance of SPSS software. The results indicate that recommendation systems have a positive and significant influence on customer experience, while AI chatbots also have a positive and significant effect. Simultaneously, both variables contribute to shaping customer experience in the use of Shopee services. These findings confirm that artificial intelligence technologies play an important role in creating a more personalized, efficient, and satisfying customer experience. This study provides practical implications for e-commerce platforms to continuously optimize the quality of recommendation systems and AI chatbots as astrategic effort to enhance customer experience and maintain competitiveness.
Co-Authors Florensia, Erika Hendrata, Florence Martin, Alnov