Implementasi Geocoding Data Alamat Untuk Optimalisasi Strategi Bisnis Dalam Sistem Informasi Geografis
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Published:
Oct 9, 2019
Keywords:
Geocoding, Heat Maps, Geographic Information System
Main Article Content
Abstract
The strategic location is no longer a guarantee of the company to achieve profitability. It takes more than just a consideration of growing degree of economic and sociological factors of local communities for the agency / company to open the outlet / branch in a new place. The lack of literacy goods or services offered to potential customers around the sales area can result in loss of business while the outlet / branch established strategic place though. Geographic Information System currently has an important role in the business world and help in opening new outlets as well as to prioritize the target market segmentation. Address data assets stakeholders (clients / customers or suppliers or distributors) owned can be optimized to support the business strategy. By using geocoding and data viewer heat maps, the address data can be used to display a blank-spot area where the target market segmentation needs to be done and be considered for the establishment of outlet / branch new.
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How to Cite
Ekawati, R. (2019). Implementasi Geocoding Data Alamat Untuk Optimalisasi Strategi Bisnis Dalam Sistem Informasi Geografis. KILAT, 5(1), 66–72. https://doi.org/10.33322/kilat.v5i1.682
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References
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Daniel W.G. & Myles G.C., 2013, The Effect of Administrative Boundaries and Geocoding Error on Cancer Rates in California, International Journal of National Institutes of Health, 3(1): 39–54, Elsevier Pubs. [11]
Hua Zhong & Bin Zhou, 2011, Using Information Technology to Optimize Operations of Third-Party Logistics Provider, International Journal of Management & Information Systems – First Quarter 2011 Volume 15, Number 1. [3]
Kavita KM, Prof Dr. & Gouri Patil, Prof., 2011, Geographic Information System (GIS) – for Business Analytics, International Journal of Scientific & Engineering Research, Volume 2, Issue 11, November-2011, ISSN 2229-5518. [1]
Pascal N., Dennis Z. & A. Zipf, 2012, The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011, International Journal of Future Internet, 4/1-21, ISSN: 1999-5903. [7]
Risma Ekawati & Suharjito, 2015, Thematic Mapping Visualization of Geographic Information System using API Fusion Tables and Google Maps Integration, Proceedings The 10thInternational Conference on Knowledge Information and Creativity Support Systems (KICSS 2015), p.513-524, ISBN: 978-974-466-838-7. [19]
Rongjian L., Marco D.A & Hanan S., 2014, Spatio-Temporal Disease Tracking Using News Articles, International Workshop on Use of GIS in Public Health, ACM SIGSPATIAL Pubs. [15]
S. Mishra & P. Chandekar, 2013, Study of Geographical Information System and its Applications, International Journal of Environmental Engineering and Management, Volume 4, Number 5, pp. 451-456, ISSN: 2231-1319. [10]
Shilin Z. et al, 2014, Advanced Heat Map and Clustering Analysis Using Heatmap3, BioMed Research International, Volume 2014, Article ID 986048, Hindawi Publishing Corporation. [13]
Soumi G. & Sanjay K.D, 2013, Comparative Analysis of K-Means and Fuzzy C-Means Algorithms, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No.4/35. [9]
Thivanka C.W. & Jing Z., 2015, Location Based Marketing: A Promising Marketing in Sri Lanka, International Journal of Marketing Studies; Vol. 7, No. 5, E-ISSN: 1918-7203. [16]
Tinashe S.C., 2014, Crime Prediction: Integration of Data Mining Techniques (Clustering and Classification) to Enhance Crime Prevention Through Analysis of the Relationships Between Type of Crimes, Locations, Times and Weather Patterns, Dissertation: National College of Ireland. [14]
Venkatesh.J, Priya.S & Aarthy. C, 2012, GIS in Indian Retail Industry-A Deliberate Tool, IRACST - International Journal of Computer Science and Information Technology & Security (IJCSITS), Vol. 2, No.3, June 2012, ISSN: 2249-9555. [5]