Issue

Vol. 7, No. 4, November 2022

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Bibliometrics Analysis and Research Profiling to Solve User Experience Overload Information

https://doi.org/10.22219/kinetik.v7i4.1575
Wahyu Andhyka Kusuma
Universitas Muhammadiyah Malang
http://orcid.org/0000-0002-1229-8495
Azrul Hazri bin Jantan
Universiti Putra Malaysia
Rusli bin Abdullah
Universiti Putra Malaysia
Novia Indriaty Admodisastro
Universiti Putra Malaysia
Noris binti Mohd Norowi
Universiti Putra Malaysia
Evi Dwi Wahyuni
Universitas Muhammadiyah Malang
Siti Alfiyatun Ni’mah
Universitas Muhammadiyah Malang

Corresponding Author(s) : Wahyu Andhyka Kusuma

kusuma.wahyu.a@gmail.com

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 7, No. 4, November 2022

Abstract

Today's technology is not just a tool to help humans perform complex tasks but has an impact on the revolutionary changes in human thought and behavior as well as culture and societal civilization that we need to know and follow, such as the current development of UX design, UX is a type of work-related to how to increase the satisfaction of application users and site visitors seen from the value for benefits, also the pleasure that the user gets from an application or site. UX is also a pattern that requires the industry and researchers to think that the human factor is more than just maintaining the user's functional needs, moreover, UX brings the concept that the user is a user. UX research is needed on the relationship between systems and interactive experiences learning about cross-disciplinary research experiences using large-scale research profiling studies and bibliometric analysis. People who use systems experiences are becoming more and more important, and because of this, interactive technologies are becoming more and more important in these experiences. Research studies show that the number of publications is growing rapidly indicating a growing scientific interest in experiential research.

Keywords

Bibliometric Analysis Research Profiling User Experience Overload Information
Kusuma, W. A., bin Jantan, A. H., bin Abdullah, R., Admodisastro, N. I., Mohd Norowi, N. binti, Wahyuni, E. D., & Ni’mah, S. A. (2022). Bibliometrics Analysis and Research Profiling to Solve User Experience Overload Information. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 7(4). https://doi.org/10.22219/kinetik.v7i4.1575
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. R. Fierley and S. Engl, “User experience methods and games: Lessons learned,” Proc. 2010 Br. Comput. Soc. Conf. Hum.-Comput. Interact. BCS-HCI 2010, pp. 204–210, 2010. https://doi.org/10.14236/ewic/hci2010.26
  2. S. Pasupa and N. Cheramakara, “Airline E-commerce user experience experiment: An investigation of Thai LCCs passengers’ purchasing behaviour among different online platforms,” J. Airl. Airpt. Manag., vol. 9, no. 2, p. 46, 2019. http://dx.doi.org/10.3926/jairm.124
  3. S. E. Chung and H. Y. Ryoo, “Study on the Level Value Standard of the Robot Appearance Interface Factor for User Experience Design,” Int. J. Adv. Sci. Technol., vol. 113, pp. 153–164, 2018. https://doi.org/10.14257/ijast.2018.113.16
  4. C.-W. Lee, G.-L. Chen, and Y.-K. Lee, “User Experience Evaluation of the EPAs-Based e-Portfolio System and an Analysis of Its Impact.,” J. Acute Med., vol. 10, no. 3, pp. 115–125, 2020. https://doi.org/10.6705/j.jacme.202009_10(3).0003
  5. C. S. Frederico, A. L. S. Pereira, C. L. Marte, and L. R. Yoshioka, “Mobile application for bus operations controlled by passengers: A user experience design project (UX),” Case Stud. Transp. Policy, vol. 9, no. 1, pp. 172–180, 2021. https://doi.org/10.1016/j.cstp.2020.11.014
  6. K. C. Brata and D. Liang, “Comparative study of user experience on mobile pedestrian navigation between digital map interface and location-based augmented reality,” Int. J. Electr. Comput. Eng., vol. 10, no. 2, pp. 2037–2044, 2020. http://doi.org/10.11591/ijece.v10i2.pp2037-2044
  7. I. Garcia-Magarino, F. Gonzalez-Landero, R. Amariglio, and J. Lloret, “Collaboration of smart IoT devices exemplified with smart cupboards,” IEEE Access, vol. 7, pp. 9881–9892, 2019. https://doi.org/10.1109/ACCESS.2018.2890393
  8. D. Duijst, “Can we Improve the User Experience of Chatbots with Personalisation ? Can we Improve the User Experience of Chatbots with Personalisation ? University of Amsterdam Master of Science,” Univ. Amst., no. July, 2017. https://doi.org/10.13140/RG.2.2.36112.92165
  9. J. Wilkinson and K. Breneman, “Bridging the Digital and the Physical User Experience: Analysis of Academic Library Floor Plans,” J. Web Librariansh., vol. 0, no. 0, pp. 28–51, 2020. https://doi.org/10.1080/19322909.2020.1788497
  10. Y. Shin, C. Im, H. Oh, and J. Kim, “Design for experience innovation: understanding user experience in new product development,” Behav. Inf. Technol., vol. 36, no. 12, pp. 1218–1234, 2017. https://doi.org/10.1080/0144929X.2017.1368709
  11. S. Filippi and B. Motyl, “Define and exploit guidelines for interactive redesign of products’ User eXperience,” Int. J. Interact. Des. Manuf., vol. 15, no. 1, pp. 51–54, 2021. https://doi.org/10.1007/s12008-020-00718-0
  12. G. Verhulsdonck and N. Shalamova, “Creating Content That Influences People: Considering User Experience and Behavioral Design in Technical Communication,” J. Tech. Writ. Commun., vol. 50, no. 4, pp. 376–400, 2020. https://doi.org/10.1177/0047281619880286
  13. P. Kiefer, I. Giannopoulos, V. Athanasios Anagnostopoulos, J. Schöning, and M. Raubal, “Controllability matters: The user experience of adaptive maps,” GeoInformatica, vol. 21, no. 3, pp. 619–641, 2017. https://doi.org/10.1007/s10707-016-0282-x
  14. M. Schrepp, A. Hinderks, and J. Thomaschewski, “Construction of a Benchmark for the User Experience Questionnaire (UEQ),” Int. J. Interact. Multimed. Artif. Intell., vol. 4, no. 4, p. 40, 2017. https://doi.org/10.9781/ijimai.2017.445
  15. L. Trautmann, A. Piros, and J. Botzheim, “Application of the fuzzy system for an emotional pattern generator,” Appl. Sci. Switz., vol. 10, no. 19, pp. 1–18, 2020. https://doi.org/10.3390/app10196930
  16. L. C. A. Gutierrez, J. M. Gutierrez, and M. S. Del-Rio-Guerra, “Having a smarter city through digital urban interfaces: An evaluation method,” Appl. Sci. Switz., vol. 9, no. 17, 2019. https://doi.org/10.3390/app9173498
  17. R. D. Munthe, K. C. Brata, and L. Fanani, “Analisis User Experience Aplikasi Mobile Facebook (Studi Kasus pada Mahasiswa Universitas Brawijaya),” J. Pengemb. Teknol. Inf. Dan Ilmu Komput., vol. 2, no. 7, pp. 2679–2688, 2018.
  18. H. W. Alomari, V. Ramasamy, J. D. Kiper, and G. Potvin, “A User Interface (UI) and User eXperience (UX) evaluation framework for cyberlearning environments in computer science and software engineering education,” Heliyon, vol. 6, no. 5, p. e03917, 2020. https://doi.org/10.1016/j.heliyon.2020.e03917
  19. E. Cross and S. Gullikson, “Notes on operations making a case for user experience research to drive technical services priorities,” Libr. Resources Tech. Serv., vol. 64, no. 2, pp. 89–98, 2020. https://doi.org/10.5860/lrts.64n2.89
  20. C. Gómez-Corona and D. Valentin, “An experiential culture: A review on user, product, drinking and eating experiences in consumer research,” Food Res. Int., vol. 115, no. August 2018, pp. 328–337, 2019. https://doi.org/10.1016/j.foodres.2018.11.035
  21. V. Roto, J. Bragge, Y. Lu, and D. Pacauskas, “Mapping experience research across disciplines: who, where, when,” Qual. User Exp., vol. 6, no. 1, pp. 1–26, 2021. https://doi.org/10.1007/s41233-021-00047-4
  22. I. Hussein, A. Hussain, E. O. C. Mkpojiogu, C. K. Lim, and K. L. Tan, “A current state performance framework for the evaluation of user experience design (UXD) practice in industry,” Int. J. Recent Technol. Eng., vol. 8, no. 2 Special Issue 2, pp. 206–214, 2019. https://doi.org/10.35940/ijrte.B1038.0782S219
  23. C. D. Ives et al., “Human–nature connection: a multidisciplinary review,” Curr. Opin. Environ. Sustain., vol. 26–27, no. November 2016, pp. 106–113, 2017. https://doi.org/10.1016/j.cosust.2017.05.005
  24. F. R. Isadora, B. T. Hanggara, and Y. T. Mursityo, “Perancangan User Experience Pada Aplikasi Mobile HomeCare Rumah Sakit Semen Gresik Menggunakan Metode Design Thinking,” J. Teknol. Inf. Dan Ilmu Komput., vol. 8, no. 5, p. 1057, 2021. http://dx.doi.org/10.25126/jtiik.2021844550
  25. A. Apraiz Iriarte, G. Lasa Erle, and M. Mazmela Etxabe, “Evaluating User Experience With Physiological Monitoring: a Systematic Literature Review,” Dyna New Technol., vol. 8, no. 1, p. [20 p.]-[20 p.], 2021. https://doi.org/10.6036/NT10072
  26. .[26] M. Rafat Odeh, B. Sartawi, and J. Najjar, “User Experience and Digitally Transformed/Converted Emotions,” Int. J. Manag. Inf. Technol., vol. 10, no. 2, pp. 01–19, 2018. https://doi.org/10.5121/ijmit.2018.10201
  27. J. Bar-Ilan, “Informetrics at the beginning of the 21st century-A review,” J. Informetr., vol. 2, no. 1, pp. 1–52, 2008. https://doi.org/10.1016/j.joi.2007.11.001
  28. A. Perianes-Rodriguez, L. Waltman, and N. J. van Eck, “Constructing bibliometric networks: A comparison between full and fractional counting,” J. Informetr., vol. 10, no. 4, pp. 1178–1195, 2016. https://doi.org/10.1016/j.joi.2016.10.006
  29. J. G. Andrews et al., “What will 5G be?,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, 2014. https://doi.org/10.1109/JSAC.2014.2328098
  30. L. Luther, V. Tiberius, and A. Brem, “User experience (UX) in business, management, and psychology: A bibliometric mapping of the current state of research,” Multimodal Technol. Interact., vol. 4, no. 2, 2020. https://doi.org/10.3390/mti4020018
  31. W. Li, O. Osibogun, T. Li, M. T. Sutherland, and W. Maziak, “Changes in harm perception of ENDS and their predictors among US adolescents: findings from the population assessment of tobacco and health (PATH) study, 2013–2018,” Prev. Med., vol. 155, no. January, p. 106957, 2022. https://doi.org/10.1016/j.ypmed.2022.106957
  32. H. Thorvaldsdóttir, J. T. Robinson, and J. P. Mesirov, “Integrative Genomics Viewer (IGV): High-performance genomics data visualization and exploration,” Brief. Bioinform., vol. 14, no. 2, pp. 178–192, 2013. https://doi.org/10.1093/bib/bbs017
  33. H. Brendan McMahan, E. Moore, D. Ramage, S. Hampson, and B. Agüera y Arcas, “Communication-efficient learning of deep networks from decentralized data,” in Proc. Int. Conf. Artif. Intell. Stat., AISTATS, 2017.
  34. M. Hassenzahl and N. Tractinsky, “User experience - A research agenda,” Behav. Inf. Technol., vol. 25, no. 2, pp. 91–97, 2006. https://doi.org/10.1080/01449290500330331
  35. J. Lin, W. Yu, N. Zhang, X. Yang, H. Zhang, and W. Zhao, “A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications,” IEEE Internet Things J., vol. 4, no. 5, pp. 1125–1142, 2017. https://doi.org/10.1109/JIOT.2017.2683200
  36. K. Seaborn and D. I. Fels, “Gamification in theory and action: A survey,” Int. J. Hum. Comput. Stud., vol. 74, pp. 14–31, 2015. https://doi.org/10.1016/j.ijhcs.2014.09.006
  37. S. Deterding, K. O’Hara, M. Sicart, D. Dixon, and L. Nacke, “Gamification: Using game design elements in non-gaming contexts,” in Conf Hum Fact Comput Syst Proc, 2011, pp. 2425–2428. https://doi.org/10.1145/1979742.1979575
  38. K. Kiili, “Digital game-based learning: Towards an experiential gaming model,” Internet High. Educ., vol. 8, no. 1, pp. 13–24, 2005. https://doi.org/10.1016/j.iheduc.2004.12.001
  39. H. L. O’Brien and E. G. Toms, “What is user engagement? A conceptual framework for defining user engagement with technology,” J. Am. Soc. Inf. Sci. Technol., vol. 59, no. 6, pp. 938–955, 2008. https://doi.org/10.1002/asi.20801
  40. B. Laugwitz, T. Held, and M. Schrepp, Construction and evaluation of a user experience questionnaire, vol. 5298 LNCS. Springer Verlag, 2008, p. 76. https://doi.org/10.1007/978-3-540-89350-9_6
  41. D. Shin, “Empathy and embodied experience in virtual environment: To what extent can virtual reality stimulate empathy and embodied experience?,” Comput. Hum. Behav., vol. 78, pp. 64–73, 2018. https://doi.org/10.1016/j.chb.2017.09.012
  42. E. Li, L. Zeng, Z. Zhou, and X. Chen, “Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing,” IEEE Trans. Wirel. Commun., vol. 19, no. 1, pp. 447–457, 2020. https://doi.org/10.1109/TWC.2019.2946140
  43. Z. Xu et al., “Large-scale order dispatch in on-demand ride-hailing platforms: A learning and planning approach,” in Proc. ACM SIGKDD Int. Conf. Knowl. Discov. Data Min., 2018, pp. 905–913. https://doi.org/10.1145/3219819.3219824
  44. C.-J. Wu et al., “Machine learning at facebook: Understanding inference at the edge,” in Proc. - IEEE Int. Symp. High Perform. Comput. Archit., HPCA, 2019, pp. 331–344. https://doi.org/10.1109/HPCA.2019.00048
Read More
Download this PDF file
PDF
Statistic
Read Counter : 16 Download : 14

Downloads

Download data is not yet available.