Review of mobile application performance evaluation to enhance selection and prediction in mobile app development
In the rapidly evolving mobile application landscape, understanding user preferences and optimizing application performance are critical factors for developers and consumers alike. This study aims to provide a structured framework for analyzing mobile application research conducted between 2019 and...
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| Format: | Article |
| Language: | English |
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Institute of Information Technology, Kohat University of Science and Technology
2024
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| Online Access: | http://umpir.ump.edu.my/id/eprint/43679/ http://umpir.ump.edu.my/id/eprint/43679/1/Review%20of%20mobile%20application%20performance%20evaluation%20to%20enhance%20selection.pdf |
| _version_ | 1848826934064054272 |
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| author | Aleem, Muhammad Noorhuzaimi, Mohd Noor Ali, Ehtesham Ibrahim, Hassan Al Mamun, Mohd Abdullah Bashir, Muhammad Talha |
| author_facet | Aleem, Muhammad Noorhuzaimi, Mohd Noor Ali, Ehtesham Ibrahim, Hassan Al Mamun, Mohd Abdullah Bashir, Muhammad Talha |
| author_sort | Aleem, Muhammad |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In the rapidly evolving mobile application landscape, understanding user preferences and optimizing application performance are critical factors for developers and consumers alike. This study aims to provide a structured framework for analyzing mobile application research conducted between 2019 and 2023, categorizing efforts into predictive analytics, user sentiment analysis, and feature prioritization to streamline the processes of application selection and development. The proliferation of mobile apps and diverse user needs have created a complex environment, with users struggling to identify suitable applications and developers facing challenges in ensuring functionality and profitability. This comprehensive review synthesizes findings from the past four years, proposing an integrated structure to leverage predictive analytics for anticipating user needs, user sentiment analysis for understanding customer preferences, and feature prioritization for optimizing application development. By adopting this holistic approach, the research aims to enhance the selection process for users and improve the overall performance and profitability of mobile applications. |
| first_indexed | 2025-11-15T03:52:42Z |
| format | Article |
| id | ump-43679 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:52:42Z |
| publishDate | 2024 |
| publisher | Institute of Information Technology, Kohat University of Science and Technology |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-436792025-01-24T02:20:38Z http://umpir.ump.edu.my/id/eprint/43679/ Review of mobile application performance evaluation to enhance selection and prediction in mobile app development Aleem, Muhammad Noorhuzaimi, Mohd Noor Ali, Ehtesham Ibrahim, Hassan Al Mamun, Mohd Abdullah Bashir, Muhammad Talha QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering In the rapidly evolving mobile application landscape, understanding user preferences and optimizing application performance are critical factors for developers and consumers alike. This study aims to provide a structured framework for analyzing mobile application research conducted between 2019 and 2023, categorizing efforts into predictive analytics, user sentiment analysis, and feature prioritization to streamline the processes of application selection and development. The proliferation of mobile apps and diverse user needs have created a complex environment, with users struggling to identify suitable applications and developers facing challenges in ensuring functionality and profitability. This comprehensive review synthesizes findings from the past four years, proposing an integrated structure to leverage predictive analytics for anticipating user needs, user sentiment analysis for understanding customer preferences, and feature prioritization for optimizing application development. By adopting this holistic approach, the research aims to enhance the selection process for users and improve the overall performance and profitability of mobile applications. Institute of Information Technology, Kohat University of Science and Technology 2024-10-09 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/43679/1/Review%20of%20mobile%20application%20performance%20evaluation%20to%20enhance%20selection.pdf Aleem, Muhammad and Noorhuzaimi, Mohd Noor and Ali, Ehtesham and Ibrahim, Hassan and Al Mamun, Mohd Abdullah and Bashir, Muhammad Talha (2024) Review of mobile application performance evaluation to enhance selection and prediction in mobile app development. International Journal of Communication Networks and Information Security (IJCNIS), 16 (4). pp. 1404-1413. ISSN 2073-607X. (Published) https://ijcnis.org/index.php/ijcnis/article/view/7378 https://ijcnis.org/index.php/ijcnis/article/view/7378 |
| spellingShingle | QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering Aleem, Muhammad Noorhuzaimi, Mohd Noor Ali, Ehtesham Ibrahim, Hassan Al Mamun, Mohd Abdullah Bashir, Muhammad Talha Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title | Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title_full | Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title_fullStr | Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title_full_unstemmed | Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title_short | Review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| title_sort | review of mobile application performance evaluation to enhance selection and prediction in mobile app development |
| topic | QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/43679/ http://umpir.ump.edu.my/id/eprint/43679/ http://umpir.ump.edu.my/id/eprint/43679/ http://umpir.ump.edu.my/id/eprint/43679/1/Review%20of%20mobile%20application%20performance%20evaluation%20to%20enhance%20selection.pdf |