Analysis Of Indrive Application User Satisfaction Level In Dki Jakarta

The online ride-hailing company inDrive must understand which services to focus on to enhance user satisfaction and meet user needs. The purpose of this research is to analyze the level of user satisfaction with the inDrive application. Data collection was conducted using a questionnaire method distributed online via social media platforms such as WhatsApp, Instagram, X, and Facebook. The subjects of this study are respondents who have used the inDrive application for a minimum of 3 months, reside in DKI Jakarta, and are over 17 years old. The sample used in this study consists of 130 respondents. This research employs SPSS software version 27 and utilizes descriptive analysis techniques, validity tests with the EFA method, reliability tests, mean tests, standard deviation tests, and T-tests for data analysis and processing. The results of this study indicate that the Ease of Use dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction". system Information Arrangement are included in the "High" category of measuring the criteria score and based on the mean test score of 3.8 including the interval level "Satisfaction". The usefulness dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction". An additional section, Intention to Use dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction"

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Publication Details

Journal
Proceeding of International Student Conference on Business, Education, Economics, Accounting, and Management.
Published
2024-09-18
DOI
https://doi.org/10.21009/isc-beam.012.220
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Analysis Of Indrive Application User Satisfaction Level In Dki Jakarta

Ika Febrilia, Dewi Agustin Pratama Sari, Ashyfa Rahma
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Proceeding of International Student Conference on Business, Education, Economics, Accounting, and Management.
Data Mining and Machine Learning Applications
article

Analysis Of Indrive Application User Satisfaction Level In Dki Jakarta

Ika Febrilia, Dewi Agustin Pratama Sari, Ashyfa Rahma
article en

Abstract

The online ride-hailing company inDrive must understand which services to focus on to enhance user satisfaction and meet user needs. The purpose of this research is to analyze the level of user satisfaction with the inDrive application. Data collection was conducted using a questionnaire method distributed online via social media platforms such as WhatsApp, Instagram, X, and Facebook. The subjects of this study are respondents who have used the inDrive application for a minimum of 3 months, reside in DKI Jakarta, and are over 17 years old. The sample used in this study consists of 130 respondents. This research employs SPSS software version 27 and utilizes descriptive analysis techniques, validity tests with the EFA method, reliability tests, mean tests, standard deviation tests, and T-tests for data analysis and processing. The results of this study indicate that the Ease of Use dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction". system Information Arrangement are included in the "High" category of measuring the criteria score and based on the mean test score of 3.8 including the interval level "Satisfaction". The usefulness dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction". An additional section, Intention to Use dimension is included in the "High" category from the measurement of the criteria score and based on mean test score of 3.8 including level "Satisfaction"

Proceeding of International Student Conference on Business, Education, Economics, Accounting, and Management.Vol. 2(1)
Openalex Percentile: Top 74%
Data Mining and Machine Learning Applications
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