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Journal : Journal of Informatics, Electrical and Electronics Engineering

Analisis Kepuasan Mahasiswa Pekanbaru Pada Aplikasi Flip dengan Metode End User Computing Satisfaction (EUCS) Anggi Widya Atma Nugraha; Inggih Permana; Febi Nur Salisah; Tengku Khairil Ahsyar; M. Afdal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2439

Abstract

A Flip is a Financial Technology (fintech) company providing admin fee-free money transfer services that has been used by more than 10 million users. Along with technological developments in the financial sector, Flip must be able to compete and survive against similar service providers. Efforts that can be made to compete include measuring satisfaction levels in using Flip. The purpose of this study is to assess the level of satisfaction of Flip users so that the results of this research can be used to provide recommendations for evaluating the Flip information system. In conducting satisfaction level analysis, the End User Computing Satisfaction (EUCS) approach can be applied. EUCS is able to evaluate usage satisfaction in using information systems in the areas of content, accuracy, format, ease of use, and timeliness based on information system usage experience. The research was conducted with sample data from university student users of the Flip application in Pekanbaru City. Based on the test results, the highest result with a percentage value of 80% in the Very Satisfied category was observed in the Ease of Use variable from the Likert scale results. The average satisfaction level of Flip application users was 77% in the Satisfied category. The Classical Assumption Test results showed that in the normality test, the testing was normal, and in the multicollinearity testing, it was found that multicollinearity did not occur in the test results. In the Multiple Linear Regression Test, the variable equation result obtained was Y = 0.158 + 0.114X1 + 0.031X2 + 0.054X3 + 0.111X4 + 0.001X5. Based on the Coefficient of Determination Test results, it was found that the content variable, accuracy variable, format variable, ease of use variable, and timeliness variable were able to explain their relationship to the dependent variable and showed an influence of 53%.
Pengukuran Retensi Pelanggan Insyira Oleh-Oleh Berdasarkan Analisis Sentimen Pengguna Instagram Fiki; Inggih Permana; Febi Nur Salisah; Eki Saputra; Arif Marsal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2473

Abstract

Instagram as a social media platform has opened new opportunities for businesses to market their products creatively and efficiently. Through interactive features such as the comments section, users can express their opinions about the products or services offered. These comments contain sentiments that can be analyzed to understand customer perceptions. This study aims to measure customer retention using sentiment analysis of Instagram user comments. The comment data was collected using web scraping techniques from the Instagram page, followed by labeling using a lexicon-based approach and sentiment classification into positive, negative, and neutral categories through sentiment analysis. This analysis is linked to the concept of customer retention, which is an important strategy for maintaining long-term relationships with consumers. Furthermore, the results of customer retention analysis in this study show that positive sentiment has a retention rate of 53.4% (303 out of 567 comments), neutral sentiment 6.9% (45 out of 650 comments), and negative sentiment 15.1% (22 out of 146 comments). Overall, 370 out of 1,363 comments, or 27.1%, were categorized as contributing to retention. In terms of the proportion of sentiment contributing to total retention, positive comments dominate with 81.9% (303 out of 370). These findings suggest that although neutral comments are the most frequent, positive sentiment contributes the most to customer retention. This indicates that positive sentiment is a strong predictor of customer loyalty, highlighting the importance for companies to foster positive experiences through quality products, reliable services, and active engagement on social media. Insyira is capable of maintaining customer retention, especially from those who express positive sentiment, which reflects satisfaction with its products, services, and interactions on social media