International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Asma Rosyidah* and Isti Surjandari

Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia


Download Citation: |
Download PDF


Spatio-temporal analysis refers to the analytical technique of geographical data based on the spatial and temporal distribution of geographical objects. In business practices, implementation of spatio-temporal analysis has opportunities in providing support for strategic decision making process in resource and asset management, investment planning, customer relationship management, and marketing strategy development. Capturing the opportunities to provide support for company decision making process and strategy development, this research was conducted using spatio-temporal analysis in one of biggest fixed broadband provider in Indonesia which offers Gigabit Passive Optical Network (GPON) configuration. In this study, the analysis was conducted on the overall customer dataset and divided dataset of customers which differed based on type of customer and location environment characteristics by exploring spatially the patterns, temporal trends, and emerging hot spots of customer distribution through fishnet grid and space time cube created from GIS-based dataset of customer order. The results obtained from this study provide an overview of customer area mapping in the form of thematic map.

Keywords: Spatio-temporal analysis; geographic information system; fishnet grid; space time cube; customer area mapping.

Share this article with your colleagues



  1. [1] Haining, R. 2003. Spatial Data Analysis Theory and Practice, Cambridge University Press. New York, USA.

  2. [2] Peuquet, D. 1994. It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Annals of the Association of American Geographers, 84, 3 : 441-461.

  3. [3] Kraak, M. J. 2003. The space-time cube revisited from a geovisualization perspective. In: Proceeding of 21st International Cartographic Conference, 8 : 10-16.

  4. [4] Gatalsky, P., Andrienko, N. and Andrienko, G. 2004. Interactive analysis of event data using space-time cube. In: Proceedings of Eighth International Conference on Information Visualisation, 4 : 145-152.

  5. [5] Law, M. and Collins, A. 2016. “Getting to Know ArcGIS Pro”, Esri Press. Redlands, CA.

  6. [6] Surjandari, I. and Rosyidah, A. 2017. Fixed broadband customer area mapping using spatial analysis. In: 2017 IEEE 8th International Conference on Awareness Science and Technology, 109-114.

  7. [7] International Telecommunication Union. 2015. ICT Facts and Figures. ITU. Geneva., Accessed on 20 Feb. 2017.

  8. [8] Asosiasi Penyelenggara Jasa Internet Indonesia. 2016. Infografis Penetrasi dan Perilaku Pengguna Internet Indonesia Survey 2016, Jakarta.

  9. [9] Rosyidah, A. and Surjandari, I. 2017. Spatio-temporal analysis of fixed broadband customer acquisition. In: 2017 IEEE 8th International Conference on Awareness Science and Technology, 115-120.

  10. [10] Shimazaki, H. and Shinomoto, S. A method for selecting the bin size of a time histogram. Neural Computation, 19, 6 : 1503-1527.

  11. [11] Lane, D. M. 2017. Online statistics education: An interactive multimedia course of study. Rice University., Accessed on 20 Feb. 2017.

  12. [12] Getis, A. and Ord, J. K. 1992. The analysis of spatial association. Geographical Analysis, 24, 3 : 189-206.

  13. [13] Ord, J. K. and Getis, A. 1995. Local spatial autocorrelation statistics: distribution issues and an application. Geographical Analysis, 27, 4 : 286-306.

  14. [14] Mann, H. B. 1945. Nonparametric tests against trend. Econometrica, 13: 245-259.

  15. [15] Hamed, K.H. 2009. Exact distribution of the Mann-Kendall trend test statistic for persistent data. Journal of Hydrology, 365,1-2 : 86-94.

  16. [16] Matalas, N. C. and Sankarasubramanian, A. 2003. Effect of persistence on trend detection via regression. Water Resources Research, 39, 12 : 1342.

  17. [17] Environmental Systems Research Institute. 2016. “ArcGIS Desktop: Release 10.5”. ESRI Press. Redlands, CA. 


Received: 2018-03-21
Revised: 2019-08-31
Accepted: 2019-09-07
Available Online: 2019-09-01

Cite this article:

Rosyidah, A., Surjandari, I. 2019. Exploring customer data using Spatio-Temporal analysis: Case study of fixed broadband provider. International Journal of Applied Science and Engineering, 16, 133-147.