Text Pre-Processing For The Frequently Mentioned Criteria From Online Community Homebuyer Dataset

Authors

  • Ahmad Taufik Nursal Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Mohd Faizal Omar Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Mohd Nasrun Mohd Nawi Universiti Utara Malaysia, 06010 Sintok, Kedah,

DOI:

https://doi.org/10.3991/ijim.v15i06.20801

Keywords:

Residential, Criteria, Purchase, User-Generated Data, Text Analysis.

Abstract


Due to the competitive Malaysian residential market with a large number of residential projects that offered almost similar features lead to difficulties of residential purchasing among homebuyers. These days, homebuyers are very selective, careful, and required more time in deciding due to the high numbers of abundant, and problem residential projects in Malaysia. As a result, a high number of unsold residential projects were reported. Therefore, understanding homebuyer criteria in a residential purchase is crucially important towards successful Malasia residential projects in the long term. This paper identifies and prioritizing homebuyers criteria in mainland Penang, Malaysia from user-generated data in online property forums. 6000 data was extracted through RapidMiner software. Once data were processes, statistic analysis is used to determined and prioritize the homebuyer's criteria. The classification of criteria is made by the real estate experts.  The result of the study provides fresh insight into homebuyers' criteria. The findings should offer developers, government, potential homebuyers, and real estate agents a better understanding of homebuyers criteria in Penang, Malaysia. 

Author Biographies

Ahmad Taufik Nursal, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia

School of Quantitative Science

Mohd Faizal Omar, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia

School of Quantitative Science

Mohd Nasrun Mohd Nawi, Universiti Utara Malaysia, 06010 Sintok, Kedah,

School of Technology Management & Logistic

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Published

2021-03-30

How to Cite

Nursal, A. T., Omar, M. F., & Mohd Nawi, M. N. (2021). Text Pre-Processing For The Frequently Mentioned Criteria From Online Community Homebuyer Dataset. International Journal of Interactive Mobile Technologies (iJIM), 15(06), pp. 171–184. https://doi.org/10.3991/ijim.v15i06.20801

Issue

Vol. 15 No. 06 (2021)

Section

Papers

License

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