Abstract

This research aims to design and develop a smartphone recommendation application that can provide suggestions based on user requirements specifications. The application development method uses an Android application-based approach. This research involves the stages of analyzing user needs, designing recommendation algorithms, implementing applications, and evaluating performance. The recommendation algorithm is developed by considering user preferences for certain features in smartphones. The test results show that this application can provide recommendations that match user needs with a sufficient level of accuracy. By offering recommendations tailored to users' interests and preferences, users no longer need to manually browse app stores or conduct intensive research.

References

• R. Kasauli, E. Knauss, J. Horkoff, G. Liebel, and F. G. de Oliveira Neto, “Requirements engineering challenges and practices in large-scale agile system development,” Journal of Systems and Software, vol. 172, p. 110851, 2021.
• S. Al-Saqqa, S. Sawalha, and H. AbdelNabi, “Agile software development: Methodologies and trends.,” International Journal of Interactive Mobile Technologies, vol. 14, no. 11, 2020.
• S. Pargaonkar, “A Comprehensive Research Analysis of Software Development Life Cycle (SDLC) Agile & Waterfall Model Advantages, Disadvantages, and Application Suitability in Software Quality Engineering,” International Journal of Scientific and Research Publications (IJSRP), vol. 13, no. 08, 2023.
• R. A. Hamid et al., “How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management,” Comput Sci Rev, vol. 39, p. 100337, 2021.
• I. H. Sarker, M. M. Hoque, M. K. Uddin, and T. Alsanoosy, “Mobile data science and intelligent apps: concepts, ai-based modeling and research directions,” Mobile Networks and Applications, vol. 26, pp. 285–303, 2021.
• S. S. Goswami and D. K. Behera, “Evaluation of the best smartphone model in the market by integrating fuzzy-AHP and PROMETHEE decision-making approach,” Decision, vol. 48, pp. 71–96, 2021.
• S. Al-Saqqa, S. Sawalha, and H. AbdelNabi, “Agile software development: Methodologies and trends.,” International Journal of Interactive Mobile Technologies, vol. 14, no. 11, 2020.
• R. A. Hamid et al., “How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management,” Comput Sci Rev, vol. 39, p. 100337, 2021.
• M. Cordella, F. Alfieri, C. Clemm, and A. Berwald, “Durability of smartphones: A technical analysis of reliability and repairability aspects,” J Clean Prod, vol. 286, p. 125388, 2021.
• F. Cheng, Y. Ming, and H. Qu, “Dece: Decision explorer with counterfactual explanations for machine learning models,” IEEE Trans Vis Comput Graph, vol. 27, no. 2, pp. 1438–1447, 2020.
• Z. H. \.Ipek, A. I. C. Gözüm, S. Papadakis, and M. Kallogiannakis, “Educational Applications of the ChatGPT AI System: A Systematic Review Research.,” Educational Process: International Journal, vol. 12, no. 3, pp. 26–55, 2023.
• A. Sharma, J. S. Pandher, and G. Prakash, “Consumer confusion and decision postponement in the online tourism domain: the moderating role of self-efficacy,” Journal of Hospitality and Tourism Insights, vol. 6, no. 2, pp. 1092–1117, 2023.