Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal Journal of Digital Market and Digital Currency International Journal Research on Metaverse
Calvina Izumi
School of Management Business, Ciputra University, Surabaya, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Enhancing Customer Satisfaction and Product Quality in E-commerce through Post-Purchase Analysis using Text Mining and Sentiment Analysis Techniques in Digital Marketing Calvina Izumi; Soeltan Abdul Ghaffar; Wilbert Clarence Setiawan
Journal of Digital Market and Digital Currency Vol. 2 No. 1 (2025): Regular Issue March 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v2i1.26

Abstract

This study explores the application of text mining and sentiment analysis to enhance product quality and customer satisfaction within the e-commerce landscape. Using the Customer360Insights dataset, which comprises 236 records of customer interactions, demographic details, product information, and transactional data, we identified key drivers of negative feedback and returns. The descriptive statistics revealed a diverse customer base with an average age of 45.33 years and significant variability in monthly income ($5,470.24 ± $1,442.80). The text mining process, including tokenization and term frequency analysis, identified frequent terms such as "poor" (95 occurrences), "arrived" (92 occurrences), and "damaged" (45 occurrences). Sentiment analysis using VADER and TextBlob indicated that 80.08% of the feedback was negative, highlighting pervasive dissatisfaction. Topic modeling using Latent Dirichlet Allocation (LDA) revealed five main topics, consistently emphasizing issues like product quality and delivery timeliness. Common return reasons included poor value (55 occurrences), wrong item delivered (49 occurrences), and late arrivals (47 occurrences). These insights suggest critical areas for improvement, such as enhancing quality control, optimizing logistics, and refining pricing strategies. The findings have significant implications for digital marketing strategies, emphasizing the need for targeted interventions to improve customer satisfaction. By addressing identified issues and leveraging data-driven insights, e-commerce businesses can enhance their product offerings, optimize post-purchase support, and foster customer loyalty. Future research should validate these findings using real-world data and explore additional data mining techniques to provide a comprehensive understanding of customer satisfaction drivers.
In-Depth Analysis of Web3 Job Market: Insights from Blockchain and Cryptocurrency Employment Landscape Calvina Izumi; Taqwa Hariguna
International Journal Research on Metaverse Vol. 1 No. 1 (2024): Regular Issue June 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijrm.v1i1.4

Abstract

The emergence of Web3, underpinned by blockchain technology, has reshaped the digital realm, ushering in a decentralized and trustless internet paradigm. In this paper, we conduct an extensive analysis of the Web3 job market, leveraging data from 2000 job postings to delineate prevalent keywords, sought-after skills, prevalent job titles, and salary determinants. Our examination reveals compelling insights into the job landscape, showcasing the dominance of technical competencies such as Ethereum proficiency and software development expertise. Among the top skills sought by employers, Ethereum (371 occurrences), React (213 occurrences), NFT (213 occurrences), Java (205 occurrences), and Rust (102 occurrences) prominently feature. Moreover, our analysis uncovers the ascendancy of specialized roles in cybersecurity, technical leadership, and project management, which command premium compensation levels. Notably, security positions emerged as the highest paying roles (average salary: $153,295.86), followed by tech lead (average salary: $121,526.32) and operations (average salary: $120,396.55). These findings offer valuable insights for job seekers, employers, educators, and policymakers navigating the evolving Web3 job landscape. By delineating key trends and challenges, our study contributes to a nuanced understanding of the transformative potential of Web3 and its implications for the future of work.
Co-Authors Soeltan Abdul Ghaffar Taqwa Hariguna Wilbert Clarence Setiawan